# EXAMPLES

COMPONENT: soc
EXAMPLENAME: MultiprocessorMinimalModelExample
EXAMPLETITLE: Multiprocessor Sample Model
PRODUCT: MATLAB;SoC Blockset
DESCRIPTION:
A minimal multiprocessor model representing an TI Delfino F2837xD hardware board that contains a pair of C28x architectures processors in the same microcontroller die.


COMPONENT: soc
EXAMPLENAME: GeneratePWMWaveformsFor3PhaseDCDCConverterExample
EXAMPLETITLE: Phase-Offset Waveforms
PRODUCT: MATLAB;SoC Blockset;C2000 Microcontroller Blockset
DESCRIPTION:
Generate phase-offset PWM waveforms. You can use the phase-offset PWM waveform to drive MOSFETs in 3-phase switching power circuits, such as the interleaved DC/DC converter circuit shown in this figure. Each MOSFET pair gets driven by a PWM of the same frequency, where each branch phase is offset by 120°.


COMPONENT: soc
EXAMPLENAME: TaskManagerPrememptionExample
EXAMPLETITLE: Preemption of Low Priority Task by High Priority Task
PRODUCT: MATLAB;SoC Blockset;Simulink
DESCRIPTION:
How the task manager changes the state of two tasks, preempting the lower priority task to allow the high priority task to run.


COMPONENT: soc
EXAMPLENAME: UseIPCoreGenerationWorkflowToTargetSoCModelExample
EXAMPLETITLE: Use IP Core Generation Workflow with SoC Models
PRODUCT: MATLAB;SoC Blockset;HDL Coder
DESCRIPTION:
Use IP Core Generation workflow to deploy an SoC model on an SoC board. You will simulate, implement and verify your design on hardware.


COMPONENT: soc
EXAMPLENAME: CompareFIRFilterImplAAExample
EXAMPLETITLE: Compare FIR Filter Implementations Using socModelAnalyzer
PRODUCT: MATLAB;SoC Blockset;DSP System Toolbox;Simulink
DESCRIPTION:
Analyze and compare different implementations of a Simulink® algorithm based on the number of arithmetic operations. Use the SoC Blockset socModelAnalyzer function to generate reports that show the number of operators for different implementations of a FIR Filter using static and runtime execution.


COMPONENT: soc
EXAMPLENAME: BasicDataLoggingExample
EXAMPLETITLE: Standard Data Logging
PRODUCT: MATLAB;SoC Blockset;C2000 Microcontroller Blockset
DESCRIPTION:
Configure an SoC Blockset model to log data from hardware when the model is deployed to a TI Delfino F28379D LaunchPad. The system contains a single timer-driven task that consists of a Sine Wave block connected to a Terminator block. To log the output signal from the Sine Wave block, select the signal line, click the ellipsis, and select Enable Data Logging. This selection automatically registers this signal to be logged from the model during simulation and to be displayed to the Simulation Data Inspector. Open the model by executing this code.


COMPONENT: soc
EXAMPLENAME: MultiprocessorDataLoggingExample
EXAMPLETITLE: Multiprocessor Data Logging
PRODUCT: MATLAB;SoC Blockset;Embedded Coder;C2000 Microcontroller Blockset
DESCRIPTION:
Configure a resource intensive SoC Blockset model to log data from hardware when the model is deployed to a TI Delfino F28379D LaunchPad. The system contains two timer-driven tasks divided across two processors. Task 1 (on processor 1) consists of a Sine Wave block connected to a Terminator block and represents a high-rate, resource intensive task. An Interprocess Data Channel block connects processor 1 and 2, providing data transfer between the processors. Task 2 (on processor 2) logs signals transferred from task 1 back to Simulink.


COMPONENT: soc_system_composer
EXAMPLENAME: SystemDesignForSignalDetectorExample
EXAMPLETITLE: Systems Engineering Approach for SoC Applications
PRODUCT: MATLAB;SoC Blockset;System Composer;Simulink
DESCRIPTION:
Design a sample signal detector application on a System on Chip (SoC) platform using a systems engineering approach. The workflow in this example maps the application functions onto the selected hardware architecture.


COMPONENT: sps
EXAMPLENAME: CalculateEfficiencyAndPowerLossContributionsExample
EXAMPLETITLE: Calculate Efficiency and Power-Loss Contributions
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
How using the ee_getEfficiency function allows you to calculate both the efficiency of the circuit and the power-loss contributions of the nonload blocks based on the power that they dissipate.


COMPONENT: sps
EXAMPLENAME: CalculateDissipatedPowerLossesForTheEntireSimulationTimeExample
EXAMPLETITLE: Calculate Dissipated Power Losses for the Entire Simulation Time
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Calculate instantaneous losses based on the power dissipated and return the time series data for all time steps in the entire simulation time using the ee_getPowerLossTimeSeries function.


COMPONENT: sps
EXAMPLENAME: CalculateDissPowLossesUsingSpecificIntervalWidthExample
EXAMPLETITLE: Calculate Dissipated Power Losses Using Specific Interval Widths
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Calculate losses based on the power dissipated and return the time series data for a specific time period with averaging applied over intervals of a specified width.


COMPONENT: sps
EXAMPLENAME: EnvironmentParametersCharacterizeDiodeExample
EXAMPLETITLE: Specify Temperature on SPICE Diode Block with Environment Parameters Block
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Use the Environment Parameters block to change the temperature of a SPICE Diode block in a simple circuit.


COMPONENT: sps
EXAMPLENAME: InductionMachineWoundRotorStartUpExample
EXAMPLETITLE: Model Start-Up Control Strategy for Wound-Rotor Induction Motor
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Design a start-up control strategy with a resistor for a wound-rotor induction model using a Simscape™ Electrical™ FEM-Parameterized Induction Machine (Wound Rotor) block.


COMPONENT: sps
EXAMPLENAME: ThermocoupleQuenchingExample
EXAMPLETITLE: Measure Temperature During Quenching of Steel Using Thermocouple Block
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Use the Thermocouple block to measure the temperature of steel during quenching. During quenching, you heat the steel to a temperature above its recrystallization temperature and then rapidly cool the steel by submerging it in liquid. Because of the high temperature, you cannot use traditional temperature measurement apparatus such as thermistor-based or semiconductor-based temperature sensors or liquid thermometers. To measure temperatures in such harsh environments, industries and laboratories employ thermocouples, which convert thermal potential difference to electrical potential difference.


COMPONENT: sps
EXAMPLENAME: CalculateDissipatedPowerLossesForASpecificTimePeriodExample
EXAMPLETITLE: Calculate Dissipated Power Losses for a Specific Time Period
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Calculate instantaneous losses based on the power dissipated and return the time series data for all time steps in a specific time period using the ee_getPowerLossTimeSeries function.


COMPONENT: sps
EXAMPLENAME: TransmissionDeltaReferenceExample
EXAMPLETITLE: Model Transmission System Using Delta Reference (Three-Phase) Block
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Use a Delta Reference (Three-Phase) block to provide a reference point for delta winding in a simple model of a transmission system.


COMPONENT: sps
EXAMPLENAME: NeutralThreePhaseExample
EXAMPLETITLE: Model Generic Neutral Connection Using Neutral Port (Three-Phase) Block
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Use the Neutral Port (Three-Phase) block to model a generic earthing connection in a three-phase network with an unbalanced load. The example also shows the effects of different types of earthing connection on network voltages and highlights when to use the Neutral Port (Three-Phase), Floating Neutral (Three-Phase), or Grounded Neutral (Three-Phase) block.


COMPONENT: sps
EXAMPLENAME: InductionHobExample
EXAMPLETITLE: Simple Induction Hob Simulation
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Model a simple induction hob system using Simscape™ Electrical™ libraries. This model focuses on the electromagnetic effect of the winding coils and the eddy current effect in the cooking pot.


COMPONENT: sps
EXAMPLENAME: FaultDetectionOfAnElectricVehicleEVChargerExample
EXAMPLETITLE: Fault Detection of Electric Vehicle Charger
PRODUCT: MATLAB;Simscape Electrical;MATLAB Coder;Simscape;Simulink;Statistics and Machine Learning Toolbox
DESCRIPTION:
Analyses the fault of an electric vehicle (EV) charger using Simscape Electrical to model the grid, the converter, and its control unit. The reliability of these chargers is an important factor in their adoption. In this example, you use measurements from the grid and the DC side of the converter to detect a gate driver fault in the converter. To analyze and detect a fault, first you generate synthetic data for different conditions with and without faults. Then you use this data to train a classification algorithm using the Classification Learner App. Finally, you use the trained model to identify or detect faults in any phase and to generate the code for deployment on hardware. You can extend this model for other system level variations or noises by having a much larger and comprehensive training dataset.


COMPONENT: sps
EXAMPLENAME: CalculateEfficiencyOfACircuitForASpecificTimePeriodExample
EXAMPLETITLE: Calculate Efficiency of Circuit for Specific Time Period
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Calculate efficiency based on the power dissipated for a specific time period using the ee_getEfficiency function.


COMPONENT: sps
EXAMPLENAME: CalculateEfficiencyForACircuitExample
EXAMPLETITLE: Calculate Efficiency for Circuit
PRODUCT: MATLAB;Simscape Electrical
DESCRIPTION:
Calculate efficiency based on the power dissipated by blocks in a circuit using the ee_getEfficiency function.


COMPONENT: stateflow
EXAMPLENAME: ClutchWithEnabledSubsystemsExample
EXAMPLETITLE: Create a Simulink Based State from an Enabled Subsystem
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
To create a Simulink based state in your Stateflow chart, copy enabled subsystems from separate Simulink models. You can reuse components from Simulink models in a Stateflow chart without creating a brand new Simulink based state.


COMPONENT: stateflow
EXAMPLENAME: FixedPointConversionsExample
EXAMPLETITLE: Compare Results of Fixed-Point Arithmetic
PRODUCT: MATLAB;Stateflow;Simulink;Fixed-Point Designer
DESCRIPTION:
The difference between various implementations of fixed-point arithmetic in Stateflow charts. The model contains three charts that calculate the ratio a/b where a = 19 and b = 24. Both inputs are signed 16-digit fixed-point numbers with one fraction bit (type fixdt(1,16,1) ). They correspond to these slopes and quantized integers:


COMPONENT: stateflow
EXAMPLENAME: PoleVaulterExample
EXAMPLETITLE: Model a Pole Vaulter by Using Simulink Based States
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
This Stateflow chart models a person moving through the stages of pole vaulting by using Simulink based states.


COMPONENT: stateflow
EXAMPLENAME: FixedPointMandelbrotSetExample
EXAMPLETITLE: Compare Fixed-Point and Floating-Point Computation in Mandelbrot Set
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Explore the difference between fixed-point numbers and floating-point numbers by computing the Mandelbrot set.


COMPONENT: stateflow
EXAMPLENAME: AddSupertransitionExample
EXAMPLETITLE: Add Supertransition from Subchart
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Create a supertransition that connects a junction inside a subchart to a junction outside the subchart.


COMPONENT: stateflow
EXAMPLENAME: StateflowStructureOperationsExample
EXAMPLETITLE: Index and Assign Values to Stateflow Structures
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Access and modify the contents of a Stateflow® structure or an array of Stateflow structures. A Stateflow structure is a data type that you define from a Simulink.Bus (Simulink) object. You can use Stateflow structures to bundle data of different sizes and types together into a single data object. For more information, see Access Bus Signals Through Stateflow Structures.


COMPONENT: stateflow
EXAMPLENAME: FunctionCallInputEventExample
EXAMPLETITLE: When to Use Function-Call Input Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use a function-call input event to activate a chart when your model requires access to output data from the chart in the same time step as the function call. For example, in this model, a function-call input event activates the Looping Scheduler chart. For more information, see Schedule a Subsystem Multiple Times in a Single Step.


COMPONENT: stateflow
EXAMPLENAME: AutomaticTransmissionLegacyExample
EXAMPLETITLE: Open the Model
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Open the model old_sf_car . This model contains a function-call subsystem named Threshold Calculation and a Stateflow chart named shift_logic .


COMPONENT: stateflow
EXAMPLENAME: IdentifyChildrenExample
EXAMPLETITLE: Identify Children of Chart
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
This chart has two children, state A and a default transition. State A has four children, state A1, state A2, and two transitions.


COMPONENT: stateflow
EXAMPLENAME: FunctionCallOutputEventExample
EXAMPLETITLE: When to Use Function-Call Output Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use a function-call output event to activate a Simulink block when your model requires access to output data from the block in the same time step as the function call. For example, this model contains two function-call output events:


COMPONENT: stateflow
EXAMPLENAME: MonitorTestPointsInStateflowChartExample
EXAMPLETITLE: Monitor Test Points in Stateflow Charts
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Specify data or states as test points that you can plot using a Floating Scope and Scope Viewer (Simulink) block during simulation. You can designate states or data with these properties as test points:


COMPONENT: stateflow
EXAMPLENAME: SuperstepExample
EXAMPLETITLE: Example of Chart with Super Step Semantics
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
How super step semantics differs from default semantics. The model contains two Stateflow charts. One chart uses super step semantics. In the other, super step semantics are disabled.


COMPONENT: stateflow
EXAMPLENAME: ChangeDetectionRampExample
EXAMPLETITLE: Example of Chart with Change Detection
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
How the operators hasChanged , hasChangedFrom , and hasChangedTo detect specific changes in an input signal. In this example, a Ramp (Simulink) block sends a discrete, increasing time signal to a chart.


COMPONENT: stateflow
EXAMPLENAME: FORLoopExample
EXAMPLETITLE: For Loop Pattern
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this example, a flow chart uses a combination of transitions and connective junctions to construct a for loop.


COMPONENT: stateflow
EXAMPLENAME: MeasuringTheFrequencyResponseOfASystemExample
EXAMPLETITLE: Measure Frequency Response by Using Complex Data in Stateflow
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Emulate a spectrum analyzer that measures the frequency response of a continuous-time system driven by a complex sinusoidal signal.


COMPONENT: stateflow
EXAMPLENAME: IncorporateActiveStateOutputExample
EXAMPLETITLE: Simplify Stateflow Charts by Incorporating Active State Output
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Active state data can simplify the design of some Stateflow® charts because you do not have to maintain data that is highly correlated to the chart hierarchy. When you enable active state data, Stateflow reports state activity through an output port to Simulink® or as local data in your chart. This example shows how to simplify the design of a Stateflow chart by adding active state output data. For more information, see Monitor State Activity Through Active State Data.


COMPONENT: stateflow
EXAMPLENAME: FixCycleErrorExample
EXAMPLETITLE: Fix Cyclic Behavior in Flow Charts
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Run-time detection of cyclical behavior is limited to cases of recursion due to event broadcasts and does not extend to other types of cyclic behavior. For instance, cycle detection does not detect the infinite cycle in this flow chart. In this example, the default transition initializes the local data i to 0. The next transition segment increments i . The transition back to the first junction is valid when i is positive. Because this condition is always true, an infinite cycle results.


COMPONENT: stateflow
EXAMPLENAME: CommentOutStateExample
EXAMPLETITLE: Comment Out State
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
When you explicitly comment out a state, box, or function, you implicitly comment out all the graphical objects that it contains. For example, when you comment out state A in this chart, you also comment out its substates, A1 and A2.


COMPONENT: stateflow
EXAMPLENAME: WHILELoopExample
EXAMPLETITLE: While Loop Pattern
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this example, a flow chart combines transitions and connective junctions to construct a while loop that computes the greatest common divisor of the inputs.


COMPONENT: stateflow
EXAMPLENAME: BitwiseOperationsAndSaturationExample
EXAMPLETITLE: Bitwise Operations and Integer Overflows
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
The implicit cast used to assign the intermediate value of a bitwise operation can result in an overflow. To preserve the rightmost bits of the result and avoid unexpected behavior, disable the chart property Saturate on Integer Overflows .


COMPONENT: stateflow
EXAMPLENAME: ModelingAnElevatorSystemUsingAtomicSubchartExample
EXAMPLETITLE: Model an Elevator System by Using Atomic Subcharts
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Model a two-car elevator system by using linked atomic subcharts in Stateflow®. The elevator system consists of a Simulink® model and a user interface (UI). The model contains two Stateflow charts:


COMPONENT: stateflow
EXAMPLENAME: BangBangControllerStateTransitionTableExample
EXAMPLETITLE: Add a New State Transition Table
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this exercise, you add a state transition table to a Simulink model that contains the required Simulink blocks, except for the bang-bang controller.


COMPONENT: stateflow
EXAMPLENAME: BindFunctionCallSubsystemToStateExample
EXAMPLETITLE: Bind a Function-Call Subsystem to a State
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
This model triggers a function-call subsystem with a trigger event E that binds to a state of a chart. The model uses a fixed-step solver with a fixed-step size of 1.


COMPONENT: stateflow
EXAMPLENAME: DebounceSignalsWithFaultDetectionExample
EXAMPLETITLE: Debounce Signals with Fault Detection
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Illustrates a design pattern that uses an intermediate state to isolate transient signals. The debouncer design uses the after operator to implement absolute-time temporal logic. With this design pattern, you can also detect faults and allow your system time to recover.


COMPONENT: stateflow
EXAMPLENAME: CustomCodeConstantsVariablesFunctionsExample
EXAMPLETITLE: Integrate Custom C Code in Stateflow Charts
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use custom C code to define constants, variables, and functions that you can access in the charts in your model. For more information about integrating custom C++ code in your charts, see Access Custom C++ Code in Stateflow Charts.


COMPONENT: stateflow
EXAMPLENAME: InterleavingBehaviorFunctionCallOutputEventsExample
EXAMPLETITLE: Interleaving Behavior of Multiple Function-Call Output Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
When there are multiple broadcasts of a function-call output event in a single time step, the chart dispatches all the broadcasts in that time step. Execution of function-call subsystems is interleaved with the execution of the chart, so that output from the function-call subsystem is available immediately in the chart. For example, in this model, the Caller chart uses the function-call output event output_cmd to activate the Callee chart.


COMPONENT: stateflow
EXAMPLENAME: ExecuteChartObjectInSimulinkExample
EXAMPLETITLE: Execute Standalone Chart in a Simulink Model
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
You can execute a standalone Stateflow chart from within a Simulink model. For example, the model sf_change_model contains two Stateflow charts that use the standalone chart sf_change to count the number of ways to make change for 27 cents in two different currency systems. You can simulate the model, but the functions that execute the standalone chart do not support code generation.


COMPONENT: stateflow
EXAMPLENAME: MuxedTriggerEventsWithBindingExample
EXAMPLETITLE: Avoid Muxed Trigger Events with Binding
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Binding events gives control of a function-call subsystem to a single state in a chart. This control does not work when you allow other events to trigger the function-call subsystem through a mux. For example, this model defines two function-call events to trigger a function-call subsystem using a Mux block.


COMPONENT: stateflow
EXAMPLENAME: CopyByGroupingExample
EXAMPLETITLE: Copy and Paste by Grouping
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Group a state and copy its contents to the chart. When you group a state, box, or graphical function, you can copy and paste all the objects contained in the grouped object, as well as all the relationships among these objects. This method is the simplest way of copying and pasting objects programmatically. If a state is not grouped, copying the state does not copy any of its contents.


COMPONENT: stateflow
EXAMPLENAME: AtomicSubchartParameterExample
EXAMPLETITLE: Map Atomic Subchart Parameters to Expressions
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
For parameters in an atomic subchart, you can specify an expression that combines constants, variables in the base workspace, and parameters in the main chart.


COMPONENT: stateflow
EXAMPLENAME: AtomicSubchartMatrixExample
EXAMPLETITLE: Map Atomic Subchart Variables to the Elements of a Matrix
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
When referring to elements of a vector or matrix, regardless of the action language of the chart, use:


COMPONENT: stateflow
EXAMPLENAME: QueuingBehaviorEdgeTriggeredOutputEventsExample
EXAMPLETITLE: Queuing Behavior of Multiple Edge-Triggered Output Events
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
A chart dispatches only one broadcast of an edge-triggered output event for each time step. When there are multiple broadcasts in a single time step, the chart dispatches one broadcast and queues up the remaining broadcasts for dispatch in successive time steps. For example, in this model, the Caller chart uses the edge-triggered output event output_cmd to activate the Callee chart.


COMPONENT: stateflow
EXAMPLENAME: TetrisExample
EXAMPLETITLE: Design a Game by Using Stateflow
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Implement the game of Tetris by using a Stateflow® chart. This model is a redesigned version of the classic Stateflow demo sf_tetris . The new design incorporates these programming paradigms:


COMPONENT: stateflow
EXAMPLENAME: ModelingAnIntersectionOfTwo1wayStreetsUsingStateflowExample
EXAMPLETITLE: Model an Intersection of One-Way Streets
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Models an intersection of one-way roads controlled by a Stateflow® traffic light system. The Stateflow chart tracks the state of each traffic light by using active state output. The behavior of the traffic lights is controlled by parameters on the Stateflow mask.


COMPONENT: stateflow
EXAMPLENAME: ExportChartLevelFunctionsExample
EXAMPLETITLE: Share Functions Across Stateflow Charts
PRODUCT: MATLAB;Stateflow
DESCRIPTION:
Call exported functions from other charts in your Simulink model. This model contains a main Stateflow chart, mainChart , and two auxiliary library charts, lib1Chart and lib2Chart . Each chart contains a chart-level graphical function and has both the Export chart level functions and Treat exported functions as globally visible chart properties enabled.


COMPONENT: stateflow
EXAMPLENAME: EdgeTriggeredOutputEventExample
EXAMPLETITLE: When to Use Edge-Triggered Output Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
To activate a Simulink subsystem when your model requires regular or periodic subsystem execution, use an edge-triggered output event. For example, this model uses an edge-triggered output event to activate two triggered subsystems at regular intervals.


COMPONENT: stateflow
EXAMPLENAME: DashboardBoilerExample
EXAMPLETITLE: Monitor a Boiler with Dashboard Blocks
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this Stateflow chart, dashboard blocks are used to control the temperature setpoint for a boiler, visualize when the boiler is on or off and what mode it is operating in.


COMPONENT: stateflow
EXAMPLENAME: ApproximateFunctionCallByEdgeTriggerExample
EXAMPLETITLE: Approximate a Function Call by Using Edge-Triggered Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
If you cannot use a function-call output event, such as for HDL code generation, you can approximate a function call by using:


COMPONENT: stateflow
EXAMPLENAME: EnabledSubsystemTempLogicExample
EXAMPLETITLE: Use Absolute-Time Temporal Logic in an Enabled Subsystem
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
You can use absolute-time temporal logic in a chart that resides in a conditionally executed subsystem. When the subsystem is disabled, the chart becomes inactive and the temporal logic operator pauses while the chart is asleep. The operator does not continue to count simulation time until the subsystem is reenabled and the chart is awake.


COMPONENT: stateflow
EXAMPLENAME: AccessBusSignalsThroughStructuresExample
EXAMPLETITLE: Example of Stateflow Structures
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this example, a Stateflow chart receives a bus input signal by using the structure inbus and outputs a bus signal from the structure outbus . The input signal comes from the Simulink Bus Creator block COUNTERBUSCreator , which bundles signals from two other Bus Creator blocks. The output structure outbus connects to a Simulink Bus Selector block. Both inbus and outbus derive their type from the Simulink.Bus object COUNTERBUS . For more information about this example, see Integrate Custom Structures in Stateflow Charts.


COMPONENT: stateflow
EXAMPLENAME: AccessGlobalDataExample
EXAMPLETITLE: Store and Retrieve Global Data
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
After binding a Stateflow data object to a Simulink data store, you can store and retrieve global data in state and transition actions. The data object acts as a global variable that you reference by its symbolic name. When you store numeric values in this variable, you are writing to the Simulink data store memory. When you retrieve numeric values from this variable, you are reading from the data store memory.


COMPONENT: stateflow
EXAMPLENAME: EdgeTriggeredEventExample
EXAMPLETITLE: When to Use Edge-Triggered Input Events
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use an edge-triggered input event to activate a chart when your model requires regular or periodic chart execution. For example, in this model, an edge-triggered input event activates the Edge to Function chart at regular intervals. For more information, see Schedule a Subsystem Multiple Times in a Single Step.


COMPONENT: stateflow
EXAMPLENAME: ReuseStatesByUsingAtomicSubchartsExample
EXAMPLETITLE: Reuse a State Multiple Times in a Chart
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use linked atomic subcharts to repeat the same configuration of states and transitions multiple times in a Stateflow® chart. Atomic subcharts are not supported in standalone Stateflow charts in MATLAB®. For more information, see Create Reusable Subcomponents by Using Atomic Subcharts.


COMPONENT: stateflow
EXAMPLENAME: CarUsingDurationGettingStartedExample
EXAMPLETITLE: Simulate Chart as a Simulink Block with Temporal Conditions
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Provides another alternative for modeling the transmission system in a car. The Stateflow chart appears as a block in a Simulink model. The other blocks in the model represent related automotive components. The chart interfaces with the other blocks by sharing data through input and output connections. To open the chart, click the arrow in the bottom left corner of the Gear_logic block.


COMPONENT: stateflow
EXAMPLENAME: CoderextrinsicInAStateflowChartExample
EXAMPLETITLE: Use the coder.extrinsic Function
PRODUCT: MATLAB;Simulink;Stateflow;Symbolic Math Toolbox
DESCRIPTION:
To enable calls to the extrinsic function heaviside (Symbolic Math Toolbox) , this model uses coder.extrinsic .


COMPONENT: stateflow
EXAMPLENAME: EdgeDetectionPulseExample
EXAMPLETITLE: Example of Chart with Edge Detection
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
How the operators crossing , falling , and rising detect edges in an input signal. In this example, a Pulse Generator (Simulink) block sends a square wave to a chart.


COMPONENT: stateflow
EXAMPLENAME: InterfaceSimulinkBusSignalsIntegrateCustomCCodeExample
EXAMPLETITLE: Integrate Custom Structures in Stateflow Charts
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Use structures from custom code in a Stateflow® chart. You can define structure typed data in C code and integrate it with Stateflow structures and Simulink® buses. By sharing data with custom code, you can augment the capabilities supported by Stateflow and take advantage of your preexisting code. For more information, see Reuse Custom Code in Stateflow Charts.


COMPONENT: stateflow
EXAMPLENAME: CopyArrayOfObjectsExample
EXAMPLETITLE: Copy and Paste Array of Objects
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Copy states A1 and A2, along with the transition between them, to a new state in the chart. To preserve transition connections and containment relationships between objects, copy all the connected objects at once.


COMPONENT: stateflow
EXAMPLENAME: CustomCPlusPlusCodeExample
EXAMPLETITLE: Access Custom C++ Code in Stateflow Charts
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Integrate custom C++ code with Stateflow® charts in Simulink® models. By sharing data and functions between your custom code and your Stateflow charts, you can augment the capabilities of Stateflow and take advantage of your preexisting code. For more information, see Reuse Custom Code in Stateflow Charts.


COMPONENT: stateflow
EXAMPLENAME: ConnectiveJunctionsOneUnconditionalTransitionExample
EXAMPLETITLE: If-then-else Pattern with an Unconditional Transition
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
In this example, the transition from state Start has three connective junctions. The first two branches of the path are guarded by a condition. The last branch of the path is unconditional.


COMPONENT: stateflow
EXAMPLENAME: FaultDetectionControlLogicInAnAircraftControlSystemExample
EXAMPLETITLE: Detect Faults in Aircraft Elevator Control System
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Design a fault detection, isolation, and recovery (FDIR) application for a pair of aircraft elevators controlled by redundant actuators.


COMPONENT: stateflow
EXAMPLENAME: ConnectMATLABStructsToSimulinkBusExample
EXAMPLETITLE: Access Simulink Bus Signals in MATLAB Functions
PRODUCT: MATLAB;Stateflow;Simulink
DESCRIPTION:
Read from and write to Simulink® bus signals in a MATLAB® function by using MATLAB and Stateflow® structures. MATLAB structures enable you to bundle data of different sizes and types into a single variable. You can create a MATLAB structure to:


COMPONENT: stateflow
EXAMPLENAME: AutomaticTransmissionWithActiveStateDataExample
EXAMPLETITLE: Simulate Chart as a Simulink Block with Local Events
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
Provides a more complex design for an automatic transmission system. The Stateflow chart appears as a block in a Simulink model. The other blocks in the model represent related automotive components. The chart interfaces with the other blocks by sharing data through input and output connections. To open the chart, click the arrow in the bottom left corner of the shift_logic block.


COMPONENT: stateflow_hdlcoder_simulink
EXAMPLENAME: InitializePersistentVariableInMooreChartExample
EXAMPLETITLE: Stateflow Chart Implementing Moore Semantics
PRODUCT: MATLAB;Simulink;Stateflow
DESCRIPTION:
This model contains a Stateflow Chart with a MATLAB function that uses the first version of fcn , described previously. The MATLAB function adds the value ( 1 or -1 ) determined by the active state to the persistent variable n at each time step.


COMPONENT: stateflow_hdlcoder_simulink
EXAMPLENAME: InitializePersistentVariableSynchronousExample
EXAMPLETITLE: State Control Block in Synchronous Mode
PRODUCT: HDL Coder;MATLAB;Simulink
DESCRIPTION:
This model contains a MATLAB Function block that uses the first version of fcn , described previously. The MATLAB Function block input is a square wave, which is provided by a Sign and Sine Wave block. The MATLAB Function block adds the value of u to the persistent variable n at each time step. The model contains a State Control block where State control is set to Synchronous .


COMPONENT: stateflow_hdlcoder_simulink
EXAMPLENAME: InitializePersistentVariableNoDirectFeedthroughExample
EXAMPLETITLE: MATLAB Function Block with No Direct Feedthrough
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model contains a MATLAB Function block that uses the first version of fcn , described previously. The MATLAB Function block input is a square wave, which is provided by a Sign and Sine Wave block. The MATLAB Function block adds the value of u to the persistent variable n at each time step.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationSVMPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationSVM Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Use the ClassificationSVM Predict block for label prediction in Simulink®. The block accepts an observation (predictor data) and returns the predicted class label and class score for the observation using the trained support vector machine (SVM) classification model.


COMPONENT: stats
EXAMPLENAME: PerformLearningIncrementalClassificationLinearBlocksExample
EXAMPLETITLE: Perform Incremental Learning Using IncrementalClassificationLinear Fit and Predict Blocks
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Perform incremental learning with the IncrementalClassificationLinear Fit block and predict labels with the IncrementalClassificationLinear Predict block.


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionGPPredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionGP Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a Gaussian process (GP) regression model, and then use the RegressionGP Predict block for response prediction.


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionNeuralNetworkPredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionNeuralNetwork Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a neural network regression model, and then use the RegressionNeuralNetwork Predict block for response prediction.


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionTreePredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionTree Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Use the RegressionTree Predict block for response prediction in Simulink®. The block accepts an observation (predictor data) and returns the predicted response for the observation using the trained regression tree model.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationLinearPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationLinear Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Use the ClassificationLinear Predict block for label prediction in Simulink®. The block accepts an observation (predictor data) and returns the predicted class label and class score for the observation using the trained classification linear model.


COMPONENT: stats
EXAMPLENAME: CompressMachineLearningModelForMemoryLimitedHardwareExample
EXAMPLETITLE: Compress Machine Learning Model for Memory-Limited Hardware
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Reduce model size by feature selection, constrained Bayesian optimization, and parameter quantization.


COMPONENT: stats
EXAMPLENAME: HARDeploymentExample
EXAMPLETITLE: Human Activity Recognition Simulink Model for Smartphone Deployment
PRODUCT:
MATLAB;Statistics and Machine Learning Toolbox;Simulink;DSP System Toolbox;Signal Processing Toolbox

DESCRIPTION:
Prepare a Simulink® model that classifies human activity based on smartphone sensor signals for code generation and smartphone deployment. The example provides a Simulink models that is ready for deployment to an Android® device. After you install the required support package, train the classification model and deploy the Simulink model to the device.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationKNNPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationKNN Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a nearest neighbor classification model, and then use the ClassificationKNN Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: VerificationValidationOfMLUsingModelBasedDesignExample
EXAMPLETITLE: Verify and Validate Machine Learning Models Using Model-Based Design
DESCRIPTION: Use Simulink to verify and validate machine learning models.
PRODUCT:
MATLAB;Statistics and Machine Learning Toolbox;Audio Toolbox;DSP System Toolbox;Embedded Coder;MATLAB Coder;Signal Processing Toolbox;Simulink;Simulink Coder;Simulink Coverage;Simulink Test;Wavelet Toolbox;Fixed-Point Designer


COMPONENT: stats
EXAMPLENAME: HARFixedPointDeploymentExample
EXAMPLETITLE: Human Activity Recognition Simulink Model for Fixed-Point Deployment
DESCRIPTION: Generate code from a classification Simulink model prepared for fixed-point deployment.
PRODUCT:
MATLAB;Statistics and Machine Learning Toolbox;Simulink;Fixed-Point Designer;Signal Processing Toolbox;DSP System Toolbox


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionLinearPredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionLinear Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Use the RegressionLinear Predict block for response prediction in Simulink®. The block accepts an observation (predictor data) and returns the predicted response for the observation using the trained regression linear model.


COMPONENT: stats
EXAMPLENAME: SystemObjectsForClassificationAndCodeGenerationExample
EXAMPLETITLE: System Objects for Classification and Code Generation
PRODUCT: MATLAB;MATLAB Coder;Simulink;Statistics and Machine Learning Toolbox;Computer Vision Toolbox
DESCRIPTION:
Generate code from a System object for making predictions using a trained classification model, and use the System object in a Simulink model.


COMPONENT: stats
EXAMPLENAME: PerformLearningIncrementalRegressionLinearBlocksExample
EXAMPLETITLE: Perform Incremental Learning Using IncrementalRegressionLinear Fit and Predict Blocks
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Perform incremental learning with the IncrementalRegressionLinear Fit block and predict responses with the IncrementalRegressionLinear Predict block.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsClassificationEnsemblePredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationEnsemble Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a classification ensemble model with optimal hyperparameters, and then use the ClassificationEnsemble Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionEnsemblePredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionEnsemble Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a regression ensemble model with optimal hyperparameters, and then use the RegressionEnsemble Predict block for response prediction.


COMPONENT: stats
EXAMPLENAME: DeployRegressionNeuralNetworkModelToFPGAExample
EXAMPLETITLE: Deploy Neural Network Regression Model to FPGA/ASIC Platform
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink;HDL Coder
DESCRIPTION:
Predict in Simulink using a neural network regression model, and deploy the Simulink model to an FPGA/ASIC platform by using HDL code generation.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationNBPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationNaiveBayes Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a naive Bayes classification model, and then use the ClassificationNaiveBayes Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: IncrementalClassificationECOCFitAndPredictBlocksExample
EXAMPLETITLE: Perform Incremental Learning Using IncrementalClassificationECOC Fit and Predict Blocks
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Perform incremental learning with the IncrementalClassificationECOC Fit block and predict labels with the IncrementalClassificationECOC Predict block.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationNNPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationNeuralNetwork Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a neural network classification model, and then use the ClassificationNeuralNetwork Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: PredictResponsesUsingRegressionSVMPredictBlockExample
EXAMPLETITLE: Predict Responses Using RegressionSVM Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a support vector machine (SVM) regression model using the Regression Learner app, and then use the RegressionSVM Predict block for response prediction.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationTreePredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationTree Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a classification decision tree model using the Classification Learner app, and then use the ClassificationTree Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationECOCPredictBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationECOC Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train an ECOC classification model, and then use the ClassificationECOC Predict block for label prediction.


COMPONENT: stats
EXAMPLENAME: PredictClassLabelsUsingClassificationDiscriminantBlockExample
EXAMPLETITLE: Predict Class Labels Using ClassificationDiscriminant Predict Block
PRODUCT: MATLAB;Statistics and Machine Learning Toolbox;Simulink
DESCRIPTION:
Train a discriminant analysis classification model, and then use the ClassificationDiscriminant Predict block for label prediction.


COMPONENT: stm32f4discovery
EXAMPLENAME: G729VoiceActivityDetectionForSTM32DiscoveryBoardExample
EXAMPLETITLE: G.729 Voice Activity Detection for STM32 Processor Based Board
PRODUCT:
MATLAB;DSP System Toolbox;Embedded Coder;MATLAB Coder;Signal Processing Toolbox;Simulink;Simulink Coder

DESCRIPTION:
Model the ITU-T G.729 Voice Activity Detector (VAD) algorithm and run it on the ARM® Cortex®-M based STMicroelectronics® STM32 boards using Embedded Coder® Support Package for STMicroelectronics STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: AsynchronousSchedulingForSTM32F4DiscoveryBoardExample
EXAMPLETITLE: Asynchronous Scheduling for STM32F4-Discovery Board
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Model asynchronous scheduling using the Hardware Interrupt block for the STMicroelectronics® STM32F4-Discovery board using Asynchronous Scheduling for STM32F4-Discovery Board using Embedded Coder® Support Package for STMicroelectronics STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: GettingStartedEmbedCoderSpkgSTMDiscoveryBoardsExample
EXAMPLETITLE: Getting Started with Embedded Coder Support Package for STMicroelectronics Discovery Boards
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Demonstrates how to use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to run a Simulink® model on an STMicroelectronics STM32F4-Discovery, STM32F746G-Discovery, or STM32F769I-Discovery board.


COMPONENT: stm32f4discovery
EXAMPLENAME: Task5ExternalModeUsingTheSTM32F4DiscoveryBoardExample
EXAMPLETITLE: External Mode Using the STM32F4-Discovery Board
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
In this task, you will run the stm32f4discovery_external_mode model in External mode. When you are prototyping and developing algorithms, it is useful to monitor signals and tune parameters while the algorithms are running on the hardware. The Simulink External mode feature enables this capability.


COMPONENT: stm32f4discovery
EXAMPLENAME: ExchangingEthernetDataWithSTM32xxBasedBoardsExample
EXAMPLETITLE: Exchanging Ethernet Data with STM32xx Based Boards
PRODUCT: MATLAB;Simulink;Simulink Coder;Embedded Coder;Instrument Control Toolbox
DESCRIPTION:
Send and receive UDP and TCP messages on STM32xx processor based boards using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: CommunicationUsingCANOrFDCANBlocksForSTM32ProcessorExample
EXAMPLETITLE: Communication Using CAN or FDCAN Blocks for STMicroelectronics STM32 Processor Based Boards
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use CAN or FDCAN blocks to communicate with the STM32 processor based boards using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors Based Boards.


COMPONENT: stm32f4discovery
EXAMPLENAME: UsingCordicCoProcessorBlockWithDMAInSTM32BoardsExample
EXAMPLETITLE: Using CORDIC Co-Processor Block with DMA in STMicroelectronics STM32 Processor Based Boards
PRODUCT: MATLAB
DESCRIPTION:
Use and generate code for a CORDIC block in a Simulink® model for STMicroelectronics® NUCLEO-G431RB board to calculate SINE and COSINE values for given values of theta by using DMA.


COMPONENT: stm32f4discovery
EXAMPLENAME: CaptureStereoPDMAudioOnSTM32ProcessorExample
EXAMPLETITLE: Capture PDM Stereo Audio on STM32 Processor
PRODUCT: MATLAB;Simulink;Embedded Coder
DESCRIPTION:
Use the I2S Mic In block in a Simulink® model to acquire Pulse Density Modulation (PDM) stereo audio data, convert it to Pulse Code Modulation (PCM) format and visualize the audio signal using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: GettingStartedWithSTM32H7xxBasedDualCoreExample
EXAMPLETITLE: Getting Started with STM32H7xx Based Dual-Core Boards
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to run a Simulink® model on a STM32 H7xx dual-core based board.


COMPONENT: stm32f4discovery
EXAMPLENAME: ExchangingWiFiDataUsingThingSpeakWithSTM32L475EExample
EXAMPLETITLE: Exchanging WiFi Data and Using ThingSpeak with STM32L475VG Discovery Board
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use Embedded Coder® Support Package for STMicroelectronics® STM32 Processors along with the STM32L475VG Discovery (B-L475E-IOT01A) board to either send and receive TCP messages or send and receive data from a ThingSpeak™ channel. ThingSpeak™ is a cloud-based MathWorks® internet of things (IoT) analytics platform. For more information, see ThingSpeak.


COMPONENT: stm32f4discovery
EXAMPLENAME: CodeVerificationAndValidationWithPILSTM32F4xxBasedBoardsExample
EXAMPLETITLE: Code Verification and Validation with PIL for STMicroelectronics STM32 Processors Based Boards
PRODUCT: MATLAB;Embedded Coder;Simulink Coder;Simulink
DESCRIPTION:
Use Embedded Coder® Support Package for STMicroelectronics® STM32 Processors for code verification and validation using Processor-in-the-Loop (PIL).


COMPONENT: stm32f4discovery
EXAMPLENAME: ExchangingEthernetDataWithTheSTM32F746GDiscoveryBoardExample
EXAMPLETITLE: Exchanging Ethernet Data with STM32F746G Discovery Board
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to run on the STM32F746G Discovery Board to send and receive the UDP and TCP messages.


COMPONENT: stm32f4discovery
EXAMPLENAME: ParametricAudioEqualizerForSTM32DiscoveryBoardsExample
EXAMPLETITLE: Parametric Audio Equalizer for STM32 Discovery Boards
PRODUCT:
MATLAB;DSP System Toolbox;Embedded Coder;MATLAB Coder;Signal Processing Toolbox;Simulink;Simulink Coder

DESCRIPTION:
Model a three band parametric equalizer algorithm and run it on the ARM® Cortex®-M based STMicroelectronics® STM32 Discovery boards using Embedded Coder® Support Package for STMicroelectronics STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: GettingStartedWithADCToSupportSTMicroelectronicsExample
PRODUCT: MATLAB;Simulink;Simulink Coder;Embedded Coder
EXAMPLETITLE:
Using the Analog to Digital Converter Block to Support STMicroelectronics STM32 Processor Based Boards

DESCRIPTION:
Use Analog to Digital Converter block in a Simulink® model to digitize analog signals connected to analog input channels using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: SignalMonitoringAndParameterTuningOfGeneratedPWMOutputExample
EXAMPLETITLE: Signal Monitoring and Parameter Tuning of Generated PWM Output
PRODUCT: MATLAB;Simulink;Embedded Coder;Simulink Coder
DESCRIPTION:
Use PWM Output block in a Simulink® model to generate PWM signals using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: GettingStartedWithSTM32F4xxBasedHardwareBoardExample
EXAMPLETITLE: Getting Started with STMicroelectronics STM32 Processor Based Boards
PRODUCT: MATLAB;Embedded Coder;Simulink Coder;Simulink
DESCRIPTION:
Use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to run a Simulink® model on an STMicroelectronics STM32 Processor Based hardware board.


COMPONENT: stm32f4discovery
EXAMPLENAME: CodeVerificationAndValidationWithPILAndExternalModeExample
EXAMPLETITLE: Code Verification and Validation with PIL and Monitoring and Tuning
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Use Embedded Coder® Support Package for STMicroelectronics® STM32 Processors for code verification and validation using PIL and Monitoring and Tuning.


COMPONENT: stm32f4discovery
EXAMPLENAME: SensorlessPMSMUsingSTM32F4xxBasedHardwareBoardExample
EXAMPLETITLE: Sensorless Field-Oriented Control of PMSM Using STM32 Processor Based Boards
PRODUCT: MATLAB;Motor Control Blockset;Simulink;Simulink Coder;Embedded Coder
DESCRIPTION:
Implements the field-oriented control (FOC) technique to control the speed of a three-phase permanent magnet synchronous motor (PMSM) based boards. For details about FOC, see Field-Oriented Control (FOC) (Motor Control Blockset).


COMPONENT: stm32f4discovery
EXAMPLENAME: UsingI2CToReadAndWriteDataOnSTM32Example
EXAMPLETITLE: Using I2C to Read and Write Data to Accelerometer on STM32 Processor Board
PRODUCT: MATLAB;Simulink;Simulink Coder;Embedded Coder
DESCRIPTION:
Configure and use I2C protocol blocks to read and write accelerometer data using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: ECGSignalProcessingUsingMQTTOnSTM32ProcessorBoardsExample
EXAMPLETITLE: ECG Signal Processing using MQTT on STM32 Processor Boards
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder;DSP System Toolbox
DESCRIPTION:
Use the STM32 Nucleo F767ZI board using Embedded Coder Support Package for STMicroelectronics STM32 Processors to process an ECG signal input from an ECG sensor, extract the heart rate in beats per minutes (bpm), and send the ECG signal and heart rate to the ThingSpeak internet of things (IoT) analytics platform service.


COMPONENT: stm32f4discovery
EXAMPLENAME: VoltageModeControlOfDCDCBuckConverterUsingSTM32Example
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
EXAMPLETITLE:
Voltage Mode Control of DC-DC Buck Converter and Boost Converter Using STMicroelectronics STM32 Processor

DESCRIPTION:
Implement a DC-DC buck converter or Boost Converter control system using the B-G474E-DPOW1 Discovery kit for Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: ReadDataFromI2CSensorsOnSTM32L475EDiscoveryBoardExample
EXAMPLETITLE: Read Data from I2C-Based Sensors on STM32L475VG Discovery Board
PRODUCT: MATLAB;Embedded Coder;Simulink;SoC Blockset
DESCRIPTION:
Use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to configure and read data from these sensors on the STM32L475VG Discovery (B-L475E-IOT01A) board:


COMPONENT: stm32f4discovery
EXAMPLENAME: UsingHardWareInterruptToCreateISRExample
EXAMPLETITLE: Using Hardware Interrupt Block to Create an ISR on STMicroelectronics STM32 Processor Based Boards
PRODUCT: Embedded Coder;MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use a Hardware Interrupt block to create an interrupt service routine (ISR) in the generated code for Embedded Coder® Support Package for STMicroelectronics® STM32 Processors Based Boards.


COMPONENT: stm32f4discovery
EXAMPLENAME: CodeOptimizationUsingCMSISDSPLibraryExample
EXAMPLETITLE: Code Optimization Using CMSIS DSP Library
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use code replacement libraries for ARM® Cortex®-M processors to generate optimized code for the STMicroelectronics® STM32F4-Discovery board using Embedded Coder® Support Package for STMicroelectronics STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: UsingSPIToReadAndWriteDataToSPIEEPROMOnSTM32ProcessorExample
EXAMPLETITLE: Using SPI to Read and Write Data to SPI EEPROM on STM32 Processor
PRODUCT: MATLAB;Embedded Coder;Simulink;Simulink Coder
DESCRIPTION:
Configure and use SPI blocks to read and write data using Embedded Coder® Support Package for STMicroelectronics® STM32 Processors.


COMPONENT: stm32f4discovery
EXAMPLENAME: MODBUSRS485CommunicationClientAndServerUsingDiscoveryExample
PRODUCT: MATLAB;Simulink;Simulink Coder;Embedded Coder
EXAMPLETITLE:
MODBUS RS485 Communication Between Client and Server Devices Using STMicroelectronics Discovery Board

DESCRIPTION:
Use the Embedded Coder® Support Package for STMicroelectronics® STM32 Processors to implement a MODBUS® RS485 asynchronous, serial communication between MODBUS client and server devices. The example also shows the four modes of operation: Client Read, Client Write, Server Read, and Server Write.


COMPONENT: stm32f4discovery
EXAMPLENAME: PushButtonAndLEDExample
EXAMPLETITLE: Push Button and LED
PRODUCT: MATLAB;Simulink;Simulink Coder
DESCRIPTION:
Use the GPIO blocks in the STMicroelectronics® STM32F4-Discovery library to control the push-button and the LED's on the STMicroelectronics® STM32F4-Discovery board.


COMPONENT: stm32f4discovery
EXAMPLENAME: EstimatePMSMParametersUsingSTM32G4BasedBoardsExample
EXAMPLETITLE: Estimate PMSM Parameters Using STM32 Processor
PRODUCT: MATLAB;Embedded Coder;Motor Control Blockset;Simulink;Simulink Coder
DESCRIPTION:
Determines the parameters of a permanent magnet synchronous motor (PMSM) using the recommended STM32xx based board. The tool determines these parameters:


COMPONENT: stm32f4discovery
EXAMPLENAME: MonitoringAndTuningSTM32F4xxBasedBoardsExample
EXAMPLETITLE: Monitoring and Tuning Using STMicroelectronics STM32 Processor Based Boards
PRODUCT: MATLAB;Embedded Coder;Simulink Coder;Simulink
DESCRIPTION:
Use Embedded Coder® Support Package for STMicroelectronics® STM32 Processors for Monitoring and Tuning simulations using STM32 processor based boards.


COMPONENT: subsystem_reference
EXAMPLENAME: DefineSSRefInterfaceUsingTestHarnessGenerateCodeExample
EXAMPLETITLE: Define Subsystem Reference Interfaces Using Test Harnesses and Generate Reusable Code
PRODUCT: MATLAB;Parallel Computing Toolbox;Simulink;Embedded Coder
DESCRIPTION:
Define interfaces and generate reusable code for subsystem reference, and how to verify that a model uses the subsystem reference correctly.


COMPONENT: subsystem_reference
EXAMPLENAME: SubsystemReferenceModelInitExample
EXAMPLETITLE: Change Subsystem Reference Component Dynamically Using InitFcn
PRODUCT: MATLAB
DESCRIPTION:
Dynamically change the subsystem reference component using the Initialization Function. InitFcn is used to change the implementation of the model without having to change the contents. This example model simulates the front and rear wipers of a vehicle. The front wiper is sensor-based and it senses rain and fog. The rear wiper is controlled by the driver.


COMPONENT: subsystem_reference
EXAMPLENAME: SubsystemReferenceDemosExample
EXAMPLETITLE: Subsystem Reference Demos
PRODUCT: MATLAB;Simulink;Embedded Coder;Parallel Computing Toolbox
DESCRIPTION:
The slexSubsystemReferenceExamples model contains a set of conceptual examples that demonstrate the capabilities of Subsystem Reference.


COMPONENT: subsystem_reference
EXAMPLENAME: SubsystemReferenceExample
EXAMPLETITLE: Reference a Subsystem File in a Model
PRODUCT: MATLAB;Simulink
DESCRIPTION:
Create and reference a subsystem file in a model. The example also demonstrates these capabilities of subsystem references:


COMPONENT: systemcomposer
EXAMPLENAME: TrafficLightExample
EXAMPLETITLE: Traffic Light Example
PRODUCT: MATLAB;System Composer;Simulink;Stateflow
DESCRIPTION:
This traffic light example contains sequence diagrams to describe pedestrians crossing an intersection. The model describes these steps:


COMPONENT: systemcomposer
EXAMPLENAME: RobotArmArchitectureExample
EXAMPLETITLE: Robot Arm Architecture Model
PRODUCT: MATLAB;System Composer;Simulink;Requirements Toolbox
DESCRIPTION:
Open the architecture model of a robot arm that consists of sensors, motion actuators, and a planning algorithm. You can use System Composer to view the interfaces and manage the requirements for this model.


COMPONENT: systemcomposer
EXAMPLENAME: InspectSequenceDiagramsProgrammaticallyExample
EXAMPLETITLE: Inspect Sequence Diagrams with Programmatic Interfaces
PRODUCT: MATLAB;Simulink;System Composer
DESCRIPTION:
Use read-only API workflows to navigate sequence diagrams in System Composer™ and display information about each of the elements.


COMPONENT: systemcomposer
EXAMPLENAME: ExtractArchitectureOfASimulinkModelExample
EXAMPLETITLE: Extract Architecture of Simulink Model Using System Composer
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
Export an existing Simulink® model to a System Composer™ architecture model. The algorithmic sections of the original model are removed and structural information is preserved during this process. Requirements links, if present, are also preserved.


COMPONENT: systemcomposer
EXAMPLENAME: ChangeStereotypeOrderProgrammaticallyExample
EXAMPLETITLE: Change Stereotype Order Programmatically
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
Change the stereotype order for stereotypes applied to components using programmatic interfaces. System Composer™ collects the stereotypes in a model from all the profiles you import into the model. When you apply multiple stereotypes to a component, stereotype-based styling, such as the component header color, is inherited from the topmost stereotype in the order. For more information on the user interface, see Change Stereotype Order Using Manage Profiles Tool.


COMPONENT: systemcomposer
EXAMPLENAME: SequenceDiagramFragmentsExample
EXAMPLETITLE: Sequence Diagram Fragments
PRODUCT: MATLAB;System Composer;Stateflow;Simulink
DESCRIPTION:
An intersection control system to demonstrate how composite fragments are used in sequence diagrams.


COMPONENT: systemcomposer
EXAMPLENAME: ACCSoftwareCompositionExample
EXAMPLETITLE: Author Functions for Software Components of Adaptive Cruise Control
PRODUCT: MATLAB;System Composer;Embedded Coder
DESCRIPTION:
Design an adaptive cruise control system in System Composer and capture its architecture with software components and functions.


COMPONENT: systemcomposer
EXAMPLENAME: ExecutionOrderSoftwareFunctionsExample
EXAMPLETITLE: Change Execution Order of Software Functions
PRODUCT: MATLAB;System Composer;Simulink;Stateflow;Embedded Coder
DESCRIPTION:
The software architecture of a throttle position control system and how to schedule the execution order of the root level functions.


COMPONENT: systemcomposer
EXAMPLENAME: UpdatingReferenceRequirementLinksExample
EXAMPLETITLE: Redirect Reference Requirement Links from Imported File
PRODUCT: MATLAB;System Composer;Requirements Toolbox
DESCRIPTION:
After importing requirement links from a file, redirect links to reference requirements in the model. When you convert the links to reference requirement links, the links are contained in the model in an SLREQX file to make full use of Requirements Toolbox™ functionality.


COMPONENT: systemcomposer
EXAMPLENAME: SoftwareArchitectureClassDiagramExample
EXAMPLETITLE: Software Architecture with Class Diagram View
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
Uses a software architecture model with functions, stereotypes, and properties to explore class diagrams in the Architecture Views Gallery. Open the model to follow the steps in this tutorial.


COMPONENT: systemcomposer
EXAMPLENAME: ArchitectureModelWithSimscapeDCMotorExample
EXAMPLETITLE: Architecture Model with Simscape Behavior for a DC Motor
PRODUCT: MATLAB;System Composer;Simscape;Simulink
DESCRIPTION:
A DC motor in an architecture model of a fan. The DC motor is modeled using a Simscape behavior within a Simulink subsystem component.


COMPONENT: systemcomposer
EXAMPLENAME: ModifyParametersForAxleArchitectureExample
EXAMPLETITLE: Modify Parameters for Axle Architecture
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
A wheel axle architecture model with instance-specific parameters exposed in System Composer™. These parameters are defined as model arguments on the Simulink® reference model used as a model behavior linked to two System Composer components. You can change the values of these parameters independently on each reference component.


COMPONENT: systemcomposer
EXAMPLENAME: ClientServerInterfacesInClassDiagramViewExample
EXAMPLETITLE: Client-Server Interfaces in Class Diagram View
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
Class diagrams display service (client-server) interfaces. The diagram shows the service interface classes and available services.


COMPONENT: systemcomposer
EXAMPLENAME: MobileRobotArchitectureExample
EXAMPLETITLE: Mobile Robot Architecture Model
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
A mobile robot architecture model with no properties defined. You can apply the stereotypes from the profile simpleProfile.xml .


COMPONENT: systemcomposer
EXAMPLENAME: UseParametersToStoreInstanceValuesExample
EXAMPLETITLE: Use Parameters to Store Instance Values with Components
PRODUCT: MATLAB;System Composer
DESCRIPTION:
Use instance-specific parameter values on referenced models to specify component parameters independently.


COMPONENT: systemcomposer
EXAMPLENAME: RobotComputerSystemsArchitectureExample
EXAMPLETITLE: Robot Computer Systems Architecture
PRODUCT: MATLAB;System Composer;Simulink
DESCRIPTION:
Use a robot computer system with controllers that simulate transmission of data to explore hierarchy diagrams in the Architecture Views Gallery.


COMPONENT: uav
EXAMPLENAME: DepthAndSegmentationVisualizationUsingUE4SimulationExample
EXAMPLETITLE: Depth and Semantic Segmentation Visualization Using Unreal Engine Simulation
PRODUCT: MATLAB;UAV Toolbox;Simulink;Computer Vision Toolbox;Simulink 3D Animation
DESCRIPTION:
Visualize depth and semantic segmentation data captured from a camera sensor in a simulation environment. This environment is rendered using the Unreal Engine® from Epic Games®.


COMPONENT: uav
EXAMPLENAME: SimulateUAVMissionInUrbanEnvironmentExample
EXAMPLETITLE: Simulate UAV Mission in Urban Environment
PRODUCT: MATLAB;UAV Toolbox
DESCRIPTION:
Create and simulate a UAV mission in an urban environment in MATLAB® and Simulink® using the uavMission and uavScenario objects, as well as OpenStreetMap® (OSM) data from Manhattan, New York. In this example, you import a plan file created in the QGroundControl app.


COMPONENT: uav
EXAMPLENAME: TuningWaypointFollowerForFixedWingUAVExample
EXAMPLETITLE: Tuning Waypoint Follower for Fixed-Wing UAV
PRODUCT: MATLAB;UAV Toolbox;Simulink
DESCRIPTION:
Design and tune a waypoint following controller for a fixed-wing UAV by using the Guidance Model and Waypoint Follower blocks.


COMPONENT: uav
EXAMPLENAME: GenerateHeadingAndYawCommandsForOrbitFollowingInSimulinkExample
EXAMPLETITLE: Generate Course and Yaw Commands for Orbit Following in Simulink®
PRODUCT: MATLAB;UAV Toolbox
DESCRIPTION:
Use the UAV Orbit Follower block to generate course and yaw commands for orbiting a location of interest with a UAV.


COMPONENT: uav
EXAMPLENAME: FlightInstrumentGaugeVisualizationForADroneExample
EXAMPLETITLE: Flight Instrument Gauge Visualization for Drone
PRODUCT: MATLAB;UAV Toolbox;Aerospace Toolbox;Aerospace Blockset
DESCRIPTION:
Import and visualize a drone flight log using 3-D animations and flight instrument gauges. This example obtains a high level overview of flight performance in MATLAB® using Flight Instruments functions in Aerospace Toolbox™. Then, to view signals in a custom interface in Simulink® , the example uses the Flight Instruments blocks from Aerospace Blockset™


COMPONENT: uav
EXAMPLENAME: MissionAndParameterProtocolInSimulinkExample
EXAMPLETITLE: Exchange Data for MAVLink Microservices like Mission Protocol and Parameter Protocol Using Simulink
PRODUCT: MATLAB;UAV Toolbox;Simulink;Stateflow;Instrument Control Toolbox
DESCRIPTION:
Implement MAVLink microservices like Mission protocol and Parameter protocol using the MAVLink Serializer and MAVLink Deserializer blocks in Simulink®.


COMPONENT: uav
EXAMPLENAME: SimulateFlightScenarioUsingSuburbanSceneInUnrealEngineExample
EXAMPLETITLE: Simulate Simple Flight Scenario Using Suburban Scene Map in Unreal Engine Environment
PRODUCT: MATLAB;UAV Toolbox
DESCRIPTION:
Download and access the Suburban scene map from the Simulation 3D Scene Configuration block. Then add a UAV vehicle and simulate a simple flight scenario in the Unreal Engine® simulation environment.


COMPONENT: uav
EXAMPLENAME: SimulateUAVWaypointFollowingWithDifferentWindConditionsExample
EXAMPLETITLE: Simulate UAV Waypoint Following with Different Wind Conditions
PRODUCT: MATLAB;UAV Toolbox;Aerospace Blockset;Aerospace Toolbox
DESCRIPTION:
Create UAV Scenario with different wind conditions and use it in Simulink® to simulate a fixed-wing UAV following waypoints.


COMPONENT: uav
EXAMPLENAME: SurveyUrbanEnvironmentUsingUAVExample
EXAMPLETITLE: Survey Urban Environment Using UAV
PRODUCT: MATLAB;UAV Toolbox
DESCRIPTION:
Specify a coverage region for a UAV and capture its flight data while surveying an urban environment. To map its environment, the UAV flies through a city and captures aerial images using a camera and other sensor data.


COMPONENT: uav
EXAMPLENAME: UAVObstacleAvoidanceInSimulinkExample
EXAMPLETITLE: UAV Obstacle Avoidance in Simulink
PRODUCT: MATLAB;UAV Toolbox
DESCRIPTION:
Simulate waypoint following mission with obstacles using the 3D VFH+ algorithm to compute obstacle-free direction.


COMPONENT: uav_lidar
EXAMPLENAME: SimulateUAVSafeLandingInUnexploredEnvironmentExample
EXAMPLETITLE: Simulate Safe Landing of UAV in Unexplored Environment Using Unreal Engine
PRODUCT: MATLAB;Simulink;Lidar Toolbox;Stateflow;Simulink 3D Animation
DESCRIPTION:
Simulate the safe landing operation of an Unmanned Aerial Vehicle (UAV) in an unexplored environment using Unreal Engine®. To safely operate in an unexplored environment, a UAV needs to have an autonomous safe landing capability. If the UAV detects a critical anomaly such as abnormalities in the battery or navigation system, the UAV must be able to scan the environment, determine a safe landing zone, and safely land without hitting any obstacle.


COMPONENT: uav_ros
EXAMPLENAME: ControlASimulatedUAVUsingROS2AndPX4BridgeExample
EXAMPLETITLE: Control a Simulated UAV Using ROS 2 and PX4 Bridge
PRODUCT: ROS Toolbox;UAV Toolbox;MATLAB
DESCRIPTION:
Receive sensor readings and autopilot status from a simulated UAV with PX4 autopilot, and send control commands to navigate the simulated UAV.


COMPONENT: usrpembeddedseriesradio
EXAMPLENAME: TransmitDataOnMultipleChannelsUsingSimulinkBlockExample
EXAMPLETITLE: Transmit Data on Multiple Channels Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to transmit data on two channels. The Channel mapping parameter of the E3xx Transmitter block is set to [1 2] . The underflow port is disabled by clearing the Enable output port for underflow indicator parameter. The Sine Wave Channel 1 block is configured to generate an 8 kHz sine wave. The Sine Wave Channel 2 block is configured to generate a 1 kHz sine wave. Both sine waves are sampled at 1 MHz. When you run this model, the E3xx Transmitter block sends the generated and combined sine waves through the air. You can inspect the generated data in the Spectrum Analyzer blocks.


COMPONENT: usrpembeddedseriesradio
EXAMPLENAME: TransmitDataOnSingleChannelUsingSimulinkBlockExample
EXAMPLETITLE: Transmit Data on Single Channel Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to transmit data on a single channel. The Channel mapping parameter of the E3xx Transmitter block is set to 1 . The underflow port is disabled by clearing the Enable output port for underflow indicator parameter. The Sine Wave block is configured to generate a 1 kHz sine wave, sampled at 1 MHz. When you run this model, the E3xx Transmitter block sends the generated sine wave through the air. You can inspect the generated data in the Spectrum Analyzer.


COMPONENT: usrpembeddedseriesradio
EXAMPLENAME: ReceiveDataOnSingleChannelUsingSimulinkBlockExample
EXAMPLETITLE: Receive Data on Single Channel Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to receive data on a single channel. The Channel mapping parameter of the E3xx Receiver block is set to 1 . The overflow port is disabled by clearing the Enable output port for overflow indicator parameter. The output data type is set to double. When you run this model, the connected Spectrum Analyzer displays the data noise received through the air. To generate an output tone, explore the Loopback parameter options on the Advanced tab. To generate a sine wave, set the Test signal injection parameter to Tone Inject Rx and the Signal generator mode to Tone .


COMPONENT: usrpembeddedseriesradio
EXAMPLENAME: ReceiveDataOnMultipleChannelsUsingSimulinkBlockExample
EXAMPLETITLE: Receive Data on Multiple Channels Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to receive data on two channels. The Channel mapping parameter of the E3xx Receiver block is set to [1 2] . The overflow port is disabled by clearing the Enable output port for overflow indicator parameter. The output data type is set to double. When you run this model, the connected Spectrum Analyzer blocks display the data noise received from the air through each channel. To generate an output tone, explore the Loopback parameter options on the Advanced tab. To generate a sine wave, set the Test signal injection parameter to Tone Inject Rx and the Signal generator mode to Tone . These settings apply to both channels.


COMPONENT: usrpradio
EXAMPLENAME: FrequencyOffsetCalibrationTransmitterUSRPHardwareExample
EXAMPLETITLE: Frequency Offset Calibration Transmitter with USRP Hardware
PRODUCT: MATLAB
DESCRIPTION:
Use the USRP™ System objects to measure and calibrate for transmitter/receiver frequency offset at the receiver.


COMPONENT: vdynblks
EXAMPLENAME: FollowWaypointsAroundOvalTrackExample
EXAMPLETITLE: Follow Waypoints Around Oval Track
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Simulate vehicle driving around oval track specified by waypoints. Model loads a minimum number of waypoints and uses a MATLAB function to determine the next heading waypoint.


COMPONENT: vdynblks
EXAMPLENAME: TrctrExample
EXAMPLETITLE: Three-Axle Tractor Towing a Three-Axle Trailer
PRODUCT: MATLAB;Vehicle Dynamics Blockset;Simulink 3D Animation
DESCRIPTION:
Simulates three-axle tractor towing a three-axle trailer for commercial trucking applications. Implements hitch subsystem, sinusoidal wave steering or braking test, and axle torque applied to tractor rear wheels.


COMPONENT: vdynblks
EXAMPLENAME: TransferTireModelParamsToSimulinkBlockExample
EXAMPLETITLE: Export Tire Model Parameter Values to Simulink Block from tireModel Object
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Export tire model parameter values to the Combined Slip Wheel 2DOF block from a tireModel object using the set method.


COMPONENT: vdynblks
EXAMPLENAME: TwoTrctrTowTwoTrailExample
EXAMPLETITLE: Two-Axle Tractor Towing a Two-Axle Trailer
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Simulate a two-axle tractor towing a two-axle trailer for a commercial trucking application. Model implements a hitch subsystem, sinusoidal wave steering input, and an axle torque applied to the rear wheels of the tractor.


COMPONENT: vdynblks
EXAMPLENAME: TrctrTowTrailExample
EXAMPLETITLE: Two-Axle Tractor Towing a One-Axle Trailer
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Simulate a two-axle tractor towing a one-axle trailer for a commercial trucking application. Model implements a hitch subsystem, sinusoidal wave steering input, and an axle torque applied to the rear wheels of the tractor.


COMPONENT: vdynblks
EXAMPLENAME: ExportTireModelParamsSimulinkToTireModelObjExample
EXAMPLETITLE: Import Tire Model Parameters from Simulink Block to TireModel Object
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Import tire model parameter values from the Dugoff Wheel 2DOF block to a tireModel object using the get method.


COMPONENT: vdynblks
EXAMPLENAME: TrctrThrExample
EXAMPLETITLE: Three-Axle Tractor Towing Two Three-Axle Trailers
PRODUCT: MATLAB;Vehicle Dynamics Blockset;Simulink 3D Animation
DESCRIPTION:
Simulate a three-axle tractor towing two three-axle trailers for a commercial trucking application. Model implements hitch subsystems, sinusoidal wave steering input, and an axle torque applied to the rear wheels of the tractor.


COMPONENT: vdynblks
EXAMPLENAME: TransferTireModelParamsToSimscapeBlockExample
EXAMPLETITLE: Export Tire Model Parameter Values to Simscape Block from tireModel Object
PRODUCT: MATLAB;Vehicle Dynamics Blockset
DESCRIPTION:
Export tire model parameter values to the Magic Formula Tire Force and Torque block from a tireModel object using the set method.


COMPONENT: vision
EXAMPLENAME: vipmosaickingExample
EXAMPLETITLE: Video Mosaicking
PRODUCT: DSP System Toolbox;MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Create a mosaic from a video sequence. Video mosaicking is the process of stitching video frames together to form a comprehensive view of the scene. The resulting mosaic image is a compact representation of the video data. The Video Mosaicking block is often used in video compression and surveillance applications.


COMPONENT: vision
EXAMPLENAME: vipconcentricityExample
EXAMPLETITLE: Concentricity Inspection
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Inspect the concentricity of both the core and the cladding in a cross-section of optical fiber. Concentricity is a measure of how centered the core is within the cladding.


COMPONENT: vision
EXAMPLENAME: vipunmarkedroadExample
EXAMPLETITLE: Color-based Road Tracking
PRODUCT: DSP System Toolbox;MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Use color information to detect and track road edges set in primarily residential settings where lane markings may not be present. The Color-based Tracking example illustrates how to use the Color Space Conversion block, the Hough Transform block, and the Kalman Filter block to detect and track information using hue and saturation.


COMPONENT: vision
EXAMPLENAME: vipmotionExample
EXAMPLETITLE: Motion Detection
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Use sum of absolute differences (SAD) method for detecting motion in a video sequence. This example applies SAD independently to four quadrants of a video sequence. If motion is detected in a quadrant, the example highlights the quadrant in red.


COMPONENT: vision
EXAMPLENAME: ReadProcessAndWriteVideoFramesExample
EXAMPLETITLE: Read, Process, and Write Video Frames to File
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Read video frames from a multimedia file, process them, and write them back to a new multimedia file.


COMPONENT: vision
EXAMPLENAME: vipldwsExample
EXAMPLETITLE: Lane Departure Warning System
PRODUCT: DSP System Toolbox;MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Detect and track road lane markers in a video sequence and notifies the driver if they are moving across a lane. The example illustrates how to use the Hough Transform, Hough Lines and Kalman Filter blocks to create a line detection and tracking algorithm. The example implements this algorithm using the following steps: 1) Detect lane markers in the current video frame. 2) Match the current lane markers with those detected in the previous video frame. 3) Find the left and right lane markers. 4) Issue a warning message if the vehicle moves across either of the lane markers.


COMPONENT: vision
EXAMPLENAME: ReplaceIntensityValuesInROIWithItsMaximumValueExample
EXAMPLETITLE: Replace Intensity Values in ROI with its Maximum Value
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Find maximum intensity value of region of interests (ROI) in the input image and replace the pixels in the ROI with its maximum value


COMPONENT: vision
EXAMPLENAME: CompareImageQualityUsingPSNRExample
EXAMPLETITLE: Compare Image Quality Using PSNR
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Compare the quality of a noisy and denoised image from the PSNR value computed using the PSNR block.


COMPONENT: vision
EXAMPLENAME: DrawHoughLinesOnAnImageExample
EXAMPLETITLE: Draw Hough Lines on Image
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Find the Cartesian coordinates of lines using rho and theta pairs, and draw those lines on an image.


COMPONENT: vision
EXAMPLENAME: vipstripesExample
EXAMPLETITLE: Periodic Noise Reduction
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Remove periodic noise from a video. In a video stream, periodic noise is typically caused by the presence of electrical or electromechanical interference during video acquisition or transmission. This type of noise is most effectively reduced with frequency domain filtering, which isolates the frequencies occupied by the noise and suppresses them using a band-reject filter.


COMPONENT: vision
EXAMPLENAME: vipstabilizeExample
EXAMPLETITLE: Video Stabilization
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Remove the effect of camera motion from a video stream. In the first video frame, the model defines the target to track. In this case, it is the back of a car and the license plate. It also establishes a dynamic search region, whose position is determined by the last known target location. The model only searches for the target within this search region, which reduces the number of computations required to find the target. In each subsequent video frame, the model determines how much the target has moved relative to the previous frame. It uses this information to remove unwanted translational camera motions and generate a stabilized video.


COMPONENT: vision
EXAMPLENAME: SelectStringToDisplayOnImageExample
EXAMPLETITLE: Select String to Insert into Image
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Select a text string and insert it into an image when the Insert Text block contains multiple text strings.


COMPONENT: vision
EXAMPLENAME: viphoughExample
EXAMPLETITLE: Rotation Correction
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Use the Hough Transform and Polyfit blocks to horizontally align text rotating in a video sequence. The techniques illustrated by this example can be used in video stabilization and optical character recognition (OCR).


COMPONENT: vision
EXAMPLENAME: vipstaplesExample
EXAMPLETITLE: Object Counting
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Use basic morphological operators to extract information from a video stream. In this case, the model counts the number of staples in each video frame. Note that the focus and lighting change in each video frame.


COMPONENT: vision
EXAMPLENAME: vipcodecExample
EXAMPLETITLE: Video Compression
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Compress a video using motion compensation and discrete cosine transform (DCT) techniques. The example calculates motion vectors between successive frames and uses them to reduce redundant information. Then it divides each frame into submatrices and applies the discrete cosine transform to each submatrix. Finally, the example applies a quantization technique to achieve further compression. The Decoder subsystem performs the inverse process to recover the original video.


COMPONENT: vision
EXAMPLENAME: FindMinimumValueInROIExample
EXAMPLETITLE: Find Minimum Value in ROI
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Calculate the minimum value in an image ROI by using the 2-D Minimum block. By using the minimum value, the model removes indistinct pixels in the image regions.


COMPONENT: vision
EXAMPLENAME: ReadAndDisplayVideoFramesExample
EXAMPLETITLE: Read and Display YCbCr Video from File
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Read video frames from a multimedia file as their luma and chrominance components, and then display them.


COMPONENT: vision
EXAMPLENAME: vipcellcountingExample
EXAMPLETITLE: Cell Counting
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Use a combination of basic morphological operators and blob analysis to extract information from a video stream. In this case, the example counts the number of E. Coli bacteria in each video frame. Note that the cells are of varying brightness, which makes the task of segmentation more challenging.


COMPONENT: vision
EXAMPLENAME: CompressImageUsing2DDCTExample
EXAMPLETITLE: Compress Image Using 2-D DCT
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Compress an image using a 2-D discrete cosine transform (DCT). The example computes the 2-D DCT of 8-by-8 nonoverlapping blocks of the input image, discards (sets to zero) all but 10 of the 64 DCT coefficients in each block, and then reconstructs the image using the 2-D inverse discrete cosine transform (IDCT) of each block.


COMPONENT: vision
EXAMPLENAME: DetectAndTrackFaceExample
EXAMPLETITLE: Detect and Track Face
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Implement a face detection and tracking algorithm in Simulink® by using a MATLAB® Function block. It closely follows the Face Detection and Tracking Using the KLT Algorithm MATLAB® example.


COMPONENT: vision
EXAMPLENAME: ReadConvertAndViewVideoFramesExample
EXAMPLETITLE: Read, Convert, and View Video from File
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Read RGB video frames from a multimedia file, convert them to intensity frames, and display them using the To Video Display block.


COMPONENT: vision
EXAMPLENAME: ComputeStandardDeviationOfROIsExample
EXAMPLETITLE: Compute Standard Deviation of ROIs
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Compute the standard deviation of regions-of-interest (ROIs) in the input image. The input image is composed of different texture regions and ROIs are selected to contain these texture regions.


COMPONENT: vision
EXAMPLENAME: vipliveedgedetectionExample
EXAMPLETITLE: Edge Detection Using Live Video Acquisition
PRODUCT: MATLAB;Computer Vision Toolbox;Image Acquisition Toolbox;Simulink
DESCRIPTION:
Use the From Video Device block provided by Image Acquisition Toolbox™ to acquire live image data from a Hamamatsu C8484 camera into Simulink®. The Prewitt method is applied to find the edges of objects in the input video stream.


COMPONENT: vision
EXAMPLENAME: viplivebarcoderecognitionExample
EXAMPLETITLE: Barcode Recognition Using Live Video Acquisition
PRODUCT: MATLAB;Computer Vision Toolbox;Image Acquisition Toolbox;Simulink
DESCRIPTION:
Use the From Video Device block provided by Image Acquisition Toolbox™ to acquire live image data from a Point Grey Flea® 2 camera into Simulink®. The example uses the Computer Vision Toolbox™ to create an image processing system which can recognize and interpret a GTIN-13 barcode. The GTIN-13 barcode, formally known as EAN-13, is an international barcode standard. It is a superset of the widely used UPC standard.


COMPONENT: vision
EXAMPLENAME: ImportImageFromSpecifiedLocationExample
EXAMPLETITLE: Import Image from Specified Location
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Import an image from a file in the specified location to Simulink workspace by using the Image From File block.


COMPONENT: vision
EXAMPLENAME: OpeningOfBinaryImageExample
EXAMPLETITLE: Perform Opening of Binary Image
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Break narrow bridges between two main sections of a binary image object and eliminate thin protruding elements.


COMPONENT: vision
EXAMPLENAME: vipscenechangeExample
EXAMPLETITLE: Scene Change Detection
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Segment video in time. The algorithm in this example can be used to detect major changes in video streams, such as when a commercial begins and ends. It can be useful when editing video or when you want to skip ahead through certain content.


COMPONENT: vision
EXAMPLENAME: vipfocusExample
EXAMPLETITLE: Video Focus Assessment
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Determine whether video frames are in focus by using the ratio of the high spatial frequency content to the low spatial frequency content within a region of interest (ROI). When this ratio is high, the video is in focus. When this ratio is low, the video is out of focus.


COMPONENT: vision
EXAMPLENAME: FindStatisticsOfCircularBlobsInImageExample
EXAMPLETITLE: Find Statistics of Circular Blobs in Image
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Find the centroid, perimeter, and bounding box coordinates of circular blobs in an image by using the Blob Analysis block. The model also outputs the label matrix for reference.


COMPONENT: vision
EXAMPLENAME: vipsurveillanceExample
EXAMPLETITLE: Surveillance Recording
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Process surveillance video to select frames that contain motion. Security concerns mandate continuous monitoring of important locations using video cameras. To efficiently record, review, and archive this massive amount of data, you can either reduce the video frame size or reduce the total number of video frames you record. This example illustrates the latter approach. In it, motion in the camera's field of view triggers the capture of "interesting" video frames.


COMPONENT: vision
EXAMPLENAME: vipabandonedobjExample
EXAMPLETITLE: Abandoned Object Detection
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox
DESCRIPTION:
Track objects at a train station and to determine which ones remain stationary. Abandoned objects in public areas concern authorities since they might pose a security risk. Algorithms, such as the one used in this example, can be used to assist security officers monitoring live surveillance video by directing their attention to a potential area of interest.


COMPONENT: vision
EXAMPLENAME: ComputeVarianceOfROIsExample
EXAMPLETITLE: Compute Variance of ROIs
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Compute the variance of regions of interest (ROIs) in the input image. The input image consists of different texture regions, and a mask image specifies ROIs selected to contain the texture regions.


COMPONENT: vision
EXAMPLENAME: GenerateImageHistogramExample
EXAMPLETITLE: Generate Image Histogram
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Generate the histogram of an image using 2-D Histogram block. The model outputs a bar plot that shows the frequency of occurrence for pixels values in the input image.


COMPONENT: vision
EXAMPLENAME: ReadAndDisplayRGBVideoFromFileExample
EXAMPLETITLE: Read and Display RGB Video from File
PRODUCT: MATLAB;Computer Vision Toolbox;Simulink
DESCRIPTION:
Read video frames from a multimedia file as their separate red, green, and blue components, and then display the video frames.


COMPONENT: vision
EXAMPLENAME: ApplyAffineTransformationToImageExample
EXAMPLETITLE: Apply Affine Transformation to Image
PRODUCT: MATLAB;Computer Vision Toolbox
DESCRIPTION:
Perform a horizontal shear transformation of an image by calculating an affine transformation matrix.


COMPONENT: vision_uav
EXAMPLENAME: StereoVisualSLAMForUAVNavigationIn3DSimulationExample
EXAMPLETITLE: Stereo Visual SLAM for UAV Navigation in 3D Simulation
PRODUCT: MATLAB;Computer Vision Toolbox;UAV Toolbox;Simulink;Navigation Toolbox;Simulink 3D Animation
DESCRIPTION:
Generate a map for a city block scene in an Unreal Engine environment using stereo visual simultaneous localization and mapping.


COMPONENT: visionhdl
EXAMPLENAME: BlobAnalysisExample
EXAMPLETITLE: Blob Analysis
DESCRIPTION: Implement a single-pass 8-way connected- component labeling algorithm and perform blob analysis.
PRODUCT:
MATLAB;Vision HDL Toolbox;Computer Vision Toolbox;Image Processing Toolbox;Fixed-Point Designer;Simulink


COMPONENT: visionhdl
EXAMPLENAME: FILSimulationWithVHTBlocksExample
EXAMPLETITLE: FPGA-in-the-Loop Simulation with Vision HDL Toolbox Blocks
PRODUCT: HDL Verifier;HDL Coder;MATLAB;Simulink;Vision HDL Toolbox
DESCRIPTION:
Modify the generated FPGA-in-the-loop (FIL) model for more efficient simulation of the Vision HDL Toolbox™ streaming video protocol.


COMPONENT: visionhdl
EXAMPLENAME: ConstructAFilterUsingLineBufferExample
EXAMPLETITLE: Construct a Filter Using Line Buffer
PRODUCT: MATLAB;Simulink;Computer Vision Toolbox;Vision HDL Toolbox;Fixed-Point Designer
DESCRIPTION:
Use the Line Buffer block to extract neighborhoods from an image for further processing. The model constructs a separable Gaussian filter.


COMPONENT: visionhdl
EXAMPLENAME: ObjectTrackingExample
EXAMPLETITLE: Object Tracking Using 2-D FFT
PRODUCT: Vision HDL Toolbox;Computer Vision Toolbox;DSP HDL Toolbox;Simulink
DESCRIPTION:
Implement an object tracking algorithm on FPGA. The model in this example supports a high frame rate of 1080p@120 fps.


COMPONENT: visionhdl
EXAMPLENAME: ImageResizeForFPGAHDLExample
EXAMPLETITLE: Change Image Size
PRODUCT: MATLAB;Simulink;Vision HDL Toolbox;HDL Coder;Computer Vision Toolbox
DESCRIPTION:
Downsample a multicomponent image by using the Image Resizer block. The example also shows how to implement custom bicubic and Lanczos-2 interpolation algorithms for FPGAs by using basic Simulink blocks.


COMPONENT: visionhdl
EXAMPLENAME: VerifySimulinkDesignUsingMATLABExample
EXAMPLETITLE: Convert MATLAB Vision Algorithm to Hardware-Targeted Simulink Model
PRODUCT: Image Processing Toolbox;MATLAB;Simulink;Vision HDL Toolbox
DESCRIPTION:
Create a hardware-targeted design in Simulink that implements the same behavior as a MATLAB reference design.


COMPONENT: visionhdl
EXAMPLENAME: DMACameraSourceExample
EXAMPLETITLE: Buffer Bursty Data Using Pixel Stream FIFO Block
PRODUCT: HDL Coder;MATLAB;Simulink;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Interface with bursty pixel streams, such as those from DMA and Camera Link® sources, using the Pixel Stream FIFO block.


COMPONENT: visionhdl
EXAMPLENAME: ImagePyramidForFPGAExample
EXAMPLETITLE: Image Pyramid
PRODUCT: MATLAB;Computer Vision Toolbox;Vision HDL Toolbox;Simulink
DESCRIPTION:
Generate multi-level image pyramid pixel streams from an input stream. This model derives multiple pixel streams by downsampling the original image in both the horizontal and vertical directions using Gaussian filtering. This type of filter avoids aliasing artifacts. The implementation uses an architecture suitable for FPGAs.


COMPONENT: visionhdl
EXAMPLENAME: MultizoneMeteringHDLExample
EXAMPLETITLE: Multi-Zone Metering
PRODUCT: HDL Coder;MATLAB;Simulink;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Use the Image Statistics block to perform multi-zone metering to extract a region of interest (ROI).


COMPONENT: visionhdl
EXAMPLENAME: SGBMDisparityHDLExample
EXAMPLETITLE: Stereo Disparity Using Semi-Global Block Matching
PRODUCT: MATLAB;Computer Vision Toolbox;Vision HDL Toolbox;Simulink
DESCRIPTION:
Compute disparity between left and right stereo camera images using the Semi-Global Block Matching algorithm. This algorithm is suitable for implementation on an FPGA.


COMPONENT: visionhdl
EXAMPLENAME: StereoImageRectificationAndSgbmFpgaExample
EXAMPLETITLE: Stereo Image Rectification and Disparity Using Semi-Global Block Matching
PRODUCT: Simulink;Fixed-Point Designer;DSP System Toolbox;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Implement stereo image rectification for a calibrated stereo camera pair and then compute disparity between the pair using the Semi-Global Block Matching algorithm. The SGBM method is an intensity-based approach and generates a dense and smooth disparity map for good 3D reconstruction. However, it is highly compute-intensive and requires hardware acceleration using FPGA to obtain real-time performance. The example modules have similar behavior in function to the Computer Vision Toolbox™ rectifyStereoImages and disparitySGM functions. This example is based on the Vision HDL Toolbox™ examples, Stereo Image Rectification and Stereo Disparity Using Semi-Global Block Matching.


COMPONENT: visionhdl
EXAMPLENAME: GammaCorrectionHDLExample
EXAMPLETITLE: Gamma Correction
PRODUCT: HDL Coder;MATLAB;Simulink;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Model pixel-streaming gamma correction for hardware designs. The model compares the results from the Vision HDL Toolbox™ Gamma Corrector block with the results generated by the full-frame Gamma block from Computer Vision Toolbox™.


COMPONENT: visionhdl
EXAMPLENAME: UsingTheLineBufferToCreateEfficientSeparableFiltersExample
EXAMPLETITLE: Using the Line Buffer to Create Efficient Separable Filters
PRODUCT: Fixed-Point Designer;MATLAB;Computer Vision Toolbox;Vision HDL Toolbox;Simulink
DESCRIPTION:
Design and implement a separable image filter, which uses fewer hardware resources than a traditional 2-D image filter.


COMPONENT: visionhdl
EXAMPLENAME: SelectRegionsForVerticalReuseExample
EXAMPLETITLE: Select Regions for Vertical Reuse
PRODUCT: MATLAB;Vision HDL Toolbox;Simulink
DESCRIPTION:
Divide a frame into tiled regions of interest (ROIs) and use those regions to configure the ROI Selector block for vertical reuse.


COMPONENT: visionhdl
EXAMPLENAME: PotHoleDetectorExample
EXAMPLETITLE: Pothole Detection
PRODUCT: MATLAB;Vision HDL Toolbox;Simulink
DESCRIPTION:
Extends the Generate Cartoon Images Using Bilateral Filtering example to include calculating a centroid and overlaying a centroid marker and text label on detected potholes.


COMPONENT: visionhdl
EXAMPLENAME: StereoImageRectificationHDLExample
EXAMPLETITLE: Stereo Image Rectification
PRODUCT: MATLAB;Vision HDL Toolbox;DSP System Toolbox;Computer Vision Toolbox;Fixed-Point Designer
DESCRIPTION:
Implement stereo image rectification for a calibrated stereo camera pair. The example model is FPGA-hardware compatible and provides real-time performance. This example compares its results with the Computer Vision Toolbox™ rectifyStereoImages function.


COMPONENT: visionhdl
EXAMPLENAME: LidarGroundSegmentationFPGAExample
EXAMPLETITLE: Ground Plane Segmentation of Lidar Data on FPGA
PRODUCT: Vision HDL Toolbox;Computer Vision Toolbox;Simulink
DESCRIPTION:
Segment organized 3-D lidar point cloud data into ground and nonground parts on FPGA. Ground plane removal is an essential video preprocessing step in lidar applications.


COMPONENT: visionhdl
EXAMPLENAME: CLAHEHDLExample
EXAMPLETITLE: Contrast Limited Adaptive Histogram Equalization
PRODUCT: MATLAB;Vision HDL Toolbox;Simulink;Computer Vision Toolbox;Fixed-Point Designer
DESCRIPTION:
Implement a contrast-limited adaptive histogram equalization (CLAHE) algorithm using Simulink® blocks. The example model is FPGA-hardware compatible.


COMPONENT: visionhdl
EXAMPLENAME: ImageRotationHDLExample
EXAMPLETITLE: Rotate Image by Small Acute Angle
DESCRIPTION: Implement an image rotation algorithm for small acute angles for FPGA.
PRODUCT:
MATLAB;Vision HDL Toolbox;DSP System Toolbox;Computer Vision Toolbox;HDL Coder;Fixed-Point Designer;Simulink


COMPONENT: visionhdl
EXAMPLENAME: NoiseRemovalAndImageSharpeningHDLExample
EXAMPLETITLE: Noise Removal and Image Sharpening
PRODUCT: HDL Coder;MATLAB;Simulink;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Implement a front-end module of an image processing design. This front-end module removes noise and sharpens the image to provide a better initial condition for the subsequent processing.


COMPONENT: visionhdl
EXAMPLENAME: MultiplePixelFilteringExample
EXAMPLETITLE: Filter Multipixel Video Streams
PRODUCT: MATLAB;Vision HDL Toolbox;Computer Vision Toolbox;Simulink
DESCRIPTION:
Design filters that operate on a multipixel input video stream. Use multipixel streaming to process high-resolution or high-frame-rate video with the same synthesized clock frequency as a single-pixel streaming interface. Multipixel streaming also improves simulation speed and throughput because fewer iterations are required to process each frame, while maintaining the hardware benefits of a streaming interface.


COMPONENT: visionhdl
EXAMPLENAME: MultiPixelMultiComponentProcessingExample
EXAMPLETITLE: MultiPixel-MultiComponent Video Streaming
PRODUCT: MATLAB;Vision HDL Toolbox;Computer Vision Toolbox;Simulink
DESCRIPTION:
Work with a multipixel-multicomponent pixel stream. Multipixel-multicomponent streaming enables real-time processing of high-resolution or high-frame-rate color video streams.


COMPONENT: visionhdl
EXAMPLENAME: FASTCornerDetectionExample
EXAMPLETITLE: FAST Corner Detection
PRODUCT: MATLAB;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Perform corner detection using the features-from-accelerated-segment test (FAST) algorithm. The algorithm is suitable for FPGAs.


COMPONENT: visionhdl
EXAMPLENAME: IntegrateVHTBlocksIntoCameraLinkSystemExample
EXAMPLETITLE: Integrate Vision HDL Blocks into Camera Link System
PRODUCT: DSP System Toolbox;MATLAB;Simulink;Vision HDL Toolbox
DESCRIPTION:
Design a Vision HDL Toolbox™ algorithm for integration into an existing system that uses the Camera Link® signal protocol.


COMPONENT: visionhdl
EXAMPLENAME: ROISelectionExample
EXAMPLETITLE: Select Region of Interest
PRODUCT: MATLAB;Vision HDL Toolbox;Computer Vision Toolbox;Simulink;HDL Coder
DESCRIPTION:
Select a region of active frame from a video stream by using the ROI Selector block from the Vision HDL Toolbox™.


COMPONENT: visionhdl_hdlcoder
EXAMPLENAME: SimulinkVisionHDLTutorialExample
EXAMPLETITLE: Design Video Processing Algorithms for HDL in Simulink
PRODUCT: MATLAB;HDL Coder;Vision HDL Toolbox;Simulink;Computer Vision Toolbox
DESCRIPTION:
Design a hardware-targeted image filter using Vision HDL Toolbox™ blocks. It also uses Computer Vision Toolbox™ blocks.


COMPONENT: visionhdl_hdlcoder
EXAMPLENAME: EdgeDetectionAndOverlayHDLExample
EXAMPLETITLE: Edge Detection and Image Overlay
PRODUCT: MATLAB;Vision HDL Toolbox;Simulink;Computer Vision Toolbox;Fixed-Point Designer
DESCRIPTION:
Detect and highlight object edges in a video stream. The behavior of the pixel-stream Sobel Edge Detector block, video stream alignment, and overlay, is verified by comparing the results with the same algorithm calculated by the full-frame blocks from the Computer Vision Toolbox™.


COMPONENT: visionhdl_hdlcoder
EXAMPLENAME: FrameBasedOpticalFlowForHDLCodeGenExample
EXAMPLETITLE: Generate HDL Code from Frame-Based Models by Using Neighborhood Modeling Methods
PRODUCT: MATLAB;HDL Coder;Simulink;Computer Vision Toolbox
DESCRIPTION:
Generate HDL code from frame-based models by using MATLAB Function blocks or the Neighborhood Processing Subsystem block.


COMPONENT: vnt
EXAMPLENAME: DevelopingAnAppDesignerAppForASimulinkModelUsingCANExample
EXAMPLETITLE: Develop an App for a Simulink Model Using CAN
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Use App Designer to construct a test application user interface (UI) and connect it to a Simulink® model using virtual CAN channels.


COMPONENT: vnt
EXAMPLENAME: CANConnectivityInARoboticsApplicationExample
EXAMPLETITLE: Implement CAN Network for Robotic Arm in Simulink
PRODUCT: MATLAB;Simscape;Simscape Multibody;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Use Vehicle Network Toolbox and Simulink to implement a Controller Area Network (CAN) in a remote manipulator arm.


COMPONENT: vnt
EXAMPLENAME: ReplayingJ1939LoggedFieldDataToASimulationExample
EXAMPLETITLE: Replay J1939 Logged Field Data to a Simulation
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Replay J1939 data from a BLF file acquired from a J1939 system in a real-world application, such as a vehicle running in the field.


COMPONENT: vnt
EXAMPLENAME: XCPDataAcquisitionInSimulinkExample
EXAMPLETITLE: Perform XCP Data Acquisition in Simulink
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Use XCP blocks to acquire measurement values in Simulink® from the XCP Sample server. The XCP Sample Server is specially designed for XCP examples only.


COMPONENT: vnt
EXAMPLENAME: MappingMDFChannelsToSimulinkModelInputPortsExample
EXAMPLETITLE: Map Channels from MDF Files to Simulink Model Input Ports
PRODUCT: MATLAB;Vehicle Network Toolbox
DESCRIPTION:
Programmatically map channels from MDF files and consume their data via input ports of a Simulink® model. It performs the gathering of input port names of a Simulink model and correlates them to the content of a given MDF file. A linkage between them is then created which consumes channel data sourced from the MDF file when the model runs.


COMPONENT: vnt
EXAMPLENAME: ClassbasedUnitTestingOfAutomotiveAlgorithmsViaCANExample
EXAMPLETITLE: Class-Based Unit Testing of Automotive Algorithms via CAN
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Validate the output of a cruise control algorithm using the Vehicle Network Toolbox™ and MATLAB® class-based unit testing framework.


COMPONENT: vnt
EXAMPLENAME: XCPOnExternalModeModelExample
EXAMPLETITLE: Perform XCP Operations on Deployed Simulink Model
PRODUCT: MATLAB;Vehicle Network Toolbox
DESCRIPTION:
Use the XCP protocol capability to perform basic XCP operation from a Simulink® model deployed to a Windows® executable. The example performs XCP operations on TCP protocol, including modifying the characteristic parameters of the model using direct memory access and reading measurement parameters of the model using direct memory access and dynamic DAQ list.


COMPONENT: vnt
EXAMPLENAME: CANConnectivityInAnAutomotiveApplicationExample
EXAMPLETITLE: Implement Distributed ECU Network over CAN in Simulink
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Use Vehicle Network Toolbox and Simulink to implement a distributed Electronic Control Unit (ECU) network over CAN for an automobile.


COMPONENT: vnt
EXAMPLENAME: BasicCANFDCommunicationExample
EXAMPLETITLE: Get Started with CAN FD Communication in Simulink
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Use MathWorks virtual CAN FD channels to set up transmission and reception of CAN FD messages in Simulink. The virtual channels are connected in a loopback configuration.


COMPONENT: vnt
EXAMPLENAME: demoVNTSL_CANReplayAndLogExample
EXAMPLETITLE: Log and Replay CAN Messages
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Log and replay CAN messages using MathWorks® Virtual CAN channels in Simulink®. You can update this model to connect to supported hardware on your system.


COMPONENT: vnt
EXAMPLENAME: EventBasedCANTransmissionInSimulinkExample
EXAMPLETITLE: Event-Based CAN Message Transmission Behavior in Simulink
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Use event-based CAN message transmission in Simulink® with Vehicle Network Toolbox™. This feature allows for CAN and CAN FD message transmission when a change in data from one time step to the next is detected.


COMPONENT: vnt
EXAMPLENAME: ProgrammaticallyBuildingModelsForCANCommunicationExample
EXAMPLETITLE: Programmatically Build Simulink Models for CAN Communication
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Programmatically construct a Simulink® model to introduce CAN or CAN FD communication using a CAN DBC file. With the add_block and set_param functions of Simulink, one can add and fully configure Vehicle Network Toolbox™ blocks to add network communication to a basic algorithm. The DBC file contains the CAN messages and signal details. The primary focus is to programmatically configure CAN and CAN FD Pack and Unpack block parameters. This can significantly increase model construction efficiency.


COMPONENT: vnt
EXAMPLENAME: GetStartedWithCANCommunicationInSimulinkExample
EXAMPLETITLE: Get Started with CAN Communication in Simulink
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Use MathWorks virtual CAN channels to set up transmission and reception of CAN messages in Simulink .


COMPONENT: vnt
EXAMPLENAME: CANFDReplayAndLogExample
EXAMPLETITLE: Log and Replay CAN FD Messages
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Log and replay CAN FD messages using MathWorks virtual CAN FD channels in Simulink. You can update this model to connect to supported hardware on your system.


COMPONENT: vnt
EXAMPLENAME: ASAMCDFXDataDictionaryExample
EXAMPLETITLE: Use CDFX Files with Simulink Data Dictionary
PRODUCT: MATLAB;Vehicle Network Toolbox
DESCRIPTION:
Store calibration data from an ASAM CDFX file in a data dictionary and use these values as parameters to a Simulink® model.


COMPONENT: vnt
EXAMPLENAME: CANMessageReceptionBehaviorInSimulinkExample
EXAMPLETITLE: CAN Message Reception Behavior in Simulink
PRODUCT: MATLAB;Vehicle Network Toolbox;Simulink
DESCRIPTION:
Observe the message processing behaviors of the CAN Receive and CAN Unpack blocks in multiple modeling scenarios. This example demonstrates two cases, with and without using the function trigger f() port of the CAN Receive block. The outputs of the model indicate the number of CAN messages unpacked for downstream processing in each case. The example uses MathWorks virtual CAN channels to send CAN messages from MATLAB to the Simulink model. These modeling practices and behavior also apply to the CAN FD protocol using the Vehicle Network Toolbox CAN FD blocks.


COMPONENT: vnt
EXAMPLENAME: demoVNTSL_CANCommunicationExample
EXAMPLETITLE: Periodic CAN Message Transmission Behavior in Simulink
PRODUCT: MATLAB;Simulink;Vehicle Network Toolbox
DESCRIPTION:
Set up periodic transmission and reception of CAN messages in Simulink® using MathWorks® virtual CAN channels. The virtual channels are connected in a loopback configuration.


COMPONENT: whdl
EXAMPLENAME: TurboDecodeStreamingSamplesExample
EXAMPLETITLE: Turbo Decode Streaming Samples
PRODUCT: LTE Toolbox;Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE Turbo Decoder block to decode data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: OFDMModulationOfLTEResourceGridSamplesExample
EXAMPLETITLE: OFDM Modulation of LTE Resource Grid Samples
PRODUCT: Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE OFDM Modulator block to modulate LTE resource grid samples to equivalent time-domain signal output.


COMPONENT: whdl
EXAMPLENAME: ConvolutionalEncodeStreamingSamplesExample
EXAMPLETITLE: Convolutional Encode of Streaming Samples
PRODUCT: LTE Toolbox;Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE Convolutional Encoder block to encode data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: ParallelGoldSequenceGenerationExample
EXAMPLETITLE: Parallel Gold Sequence Generation
PRODUCT: HDL Coder;Wireless HDL Toolbox;MATLAB;Simulink
DESCRIPTION:
Use LTE Gold Sequence Generator block to generate multiple sequences in parallel for use in channel estimation.


COMPONENT: whdl
EXAMPLENAME: ModulateDataBitsUsingGMSKExample
EXAMPLETITLE: Modulate Data Bits Using GMSK
PRODUCT: MATLAB;Wireless HDL Toolbox
DESCRIPTION:
Use GMSK Modulator block to modulate data bits to symbols using Gaussian minimum shift keying (GMSK) method.


COMPONENT: whdl
EXAMPLENAME: DecodeAndRecoverMessageFromCCSDSRSCodewordExample
EXAMPLETITLE: Decode and Recover Message from RS Codeword Using CCSDS Standard
PRODUCT: MATLAB;Wireless HDL Toolbox;Satellite Communications Toolbox;Simulink
DESCRIPTION:
Use CCSDS RS Decoder block to decode and recover message from Reed-Solomon (RS) codeword according to Consultative Committee for Space Data Systems (CCSDS) standard.


COMPONENT: whdl
EXAMPLENAME: HDLOFDMMATLABReferencesExample
EXAMPLETITLE: HDL OFDM MATLAB References
PRODUCT: MATLAB;Wireless HDL Toolbox;Simulink;HDL Coder;DSP HDL Toolbox
DESCRIPTION:
Model OFDM transmitter and receiver hardware algorithms in MATLAB as a step towards HDL-compatible Simulink model.


COMPONENT: whdl
EXAMPLENAME: HDLImplementationOfFadingChannelExample
EXAMPLETITLE: HDL Implementation of SISO Fading Channel
PRODUCT: MATLAB;Wireless HDL Toolbox;Communications Toolbox;DSP HDL Toolbox
DESCRIPTION:
Use SISO fading channel to evaluate performance of wireless communication systems over Rayleigh and Rician fading channels.


COMPONENT: whdl
EXAMPLENAME: NRLDPCEncodeAndDecodeHDLExample
EXAMPLETITLE: LDPC Encode and Decode of 5G NR Streaming Data
PRODUCT: MATLAB;Wireless HDL Toolbox;5G Toolbox
DESCRIPTION:
Simulate NR LDPC Encoder and NR LDPC Decoder blocks and compare their hardware-optimized results with results from 5G Toolbox™ functions.


COMPONENT: whdl
EXAMPLENAME: HDLNeuralNetworkDesignForDigitalPredistorterExample
EXAMPLETITLE: HDL Neural Network Design for Digital Predistorter
PRODUCT: MATLAB;Wireless HDL Toolbox;Deep Learning Toolbox
DESCRIPTION:
Use neural-network-based (NN-based) digital predistorter (DPD) to compensate effects of nonlinearities in power amplifier.


COMPONENT: whdl
EXAMPLENAME: CheckForCRCErrorsInStreamingSamplesExample
EXAMPLETITLE: Check for CRC Errors in Streaming Samples
PRODUCT: LTE Toolbox;Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE CRC Decoder block to check encoded data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: DigitalAGCHDLExample
EXAMPLETITLE: HDL Digital Automatic Gain Control for Single and Multicarrier Systems
PRODUCT: MATLAB;Wireless HDL Toolbox;DSP HDL Toolbox;HDL Coder;Simulink
DESCRIPTION:
Implement digital AGC for single-carrier and multicarrier systems using Simulink® blocks optimized for HDL code generation.


COMPONENT: whdl
EXAMPLENAME: ConvolutionalDecodeStreamingSamplesExample
EXAMPLETITLE: Convolutional Decode of Streaming Samples
PRODUCT: LTE Toolbox;Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE Convolutional Decoder block to decode data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: NRPolarEncodeAndDecodeHDLExample
EXAMPLETITLE: Polar Encode and Decode of Streaming Samples
PRODUCT: MATLAB;Wireless HDL Toolbox;5G Toolbox
DESCRIPTION:
Simulate NR Polar Encode and Decode blocks and compare the hardware-optimized results with results from 5G Toolbox™ functions.


COMPONENT: whdl
EXAMPLENAME: HDLImplementationOfDPDWithLMSCoefficientEstimationExample
EXAMPLETITLE: HDL Implementation of Digital Predistorter with LMS Coefficient Estimation
PRODUCT: Wireless HDL Toolbox;RF Blockset;DSP System Toolbox
DESCRIPTION:
Implement DPD with LMS coefficients and pre-calculated coefficients optimized for HDL code generation.


COMPONENT: whdl
EXAMPLENAME: LTEHDLCRCEncoderExample
EXAMPLETITLE: Append CRC Checksum to Streaming Data
PRODUCT: LTE Toolbox;Wireless HDL Toolbox;MATLAB
DESCRIPTION:
Use LTE CRC Encoder block to encode data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: WLANHDLFrameDetectionAndSignalBitRecoveryExample
EXAMPLETITLE: WLAN HDL 802.11ax (HE) Frame Detection and Signal Recovery
PRODUCT: MATLAB;Wireless HDL Toolbox;WLAN Toolbox
DESCRIPTION:
Implement WLAN receiver using Simulink® blocks that are optimized for HDL code generation and hardware implementation.


COMPONENT: whdl
EXAMPLENAME: NRCRCEncodeAndDecodeOfStreamingDataExample
EXAMPLETITLE: NR CRC Encode and Decode Streaming Data
PRODUCT: MATLAB;Wireless HDL Toolbox;5G Toolbox;Simulink
DESCRIPTION:
Use NR CRC Encoder and NR CRC Decoder blocks and compare their hardware-optimized results with results from 5G Toolbox™ functions.


COMPONENT: whdl
EXAMPLENAME: TurboEncodeStreamingSamplesExample
EXAMPLETITLE: Turbo Encode Streaming Samples
PRODUCT: Wireless HDL Toolbox;LTE Toolbox;MATLAB
DESCRIPTION:
Use LTE Turbo Encoder block to encode data, and how to compare hardware-friendly design with results from LTE Toolbox™.


COMPONENT: whdl
EXAMPLENAME: WLANLDPCDecodeOfStreamingDataExample
EXAMPLETITLE: Decode WLAN LDPC Streaming Data
PRODUCT: MATLAB;Wireless HDL Toolbox;WLAN Toolbox;Communications Toolbox
DESCRIPTION:
Simulate WLAN LDPC Decoder block and compare hardware-optimized results with results from Communication Toolbox™ function.


COMPONENT: whdl
EXAMPLENAME: HDLImplementationOfDigitalPreDistorterExample
EXAMPLETITLE: HDL Implementation of Digital Predistorter
PRODUCT:
MATLAB;Wireless HDL Toolbox;HDL Coder;RF Blockset;Simulink;DSP System Toolbox;Communications Toolbox

DESCRIPTION:
Implement Digital Predistorter that is optimized for HDL code generation and hardware implementation.


COMPONENT: wlan
EXAMPLENAME: HERFReceiverNRInterfererExample
EXAMPLETITLE: Modeling and Testing an 802.11ax RF Receiver with 5G Interference
PRODUCT: MATLAB;WLAN Toolbox;Simulink;RF Blockset;5G Toolbox
DESCRIPTION:
Characterize the impact of RF impairments on the RF reception of an IEEE 802.11ax waveform coexisting with an adjacent 5G or 802.11ax interferer.


COMPONENT: wlan
EXAMPLENAME: WLANMultiNodeAbstractedPHYExample
EXAMPLETITLE: 802.11ax System-Level Simulation with Physical Layer Abstraction
PRODUCT: MATLAB;WLAN Toolbox;SimEvents;Simulink;Stateflow
DESCRIPTION:
Demonstrates how to model a multi-node IEEE® 802.11ax™ [ 1 ] network with abstracted physical layer (PHY) using SimEvents®, Stateflow®, and WLAN Toolbox™. A PHY abstraction model largely reduces the complexity and the duration of system-level simulations by replacing the actual physical layer computations. This makes it possible to evaluate systems consisting of large number of nodes, resulting in increased scalability. Abstracted PHY models signal-power, gain, delay, loss and interference on each packet without generating physical layer packets, as specified by the TGax Evaluation Methodology [ 3 ].


COMPONENT: wlan
EXAMPLENAME: WLANMACThroughputMeasurementExample
EXAMPLETITLE: 802.11 MAC and Application Throughput Measurement
PRODUCT: MATLAB;WLAN Toolbox;SimEvents;Stateflow;Simulink
DESCRIPTION:
Measure the MAC and application layer throughput in a multi-node 802.11a/n/ac/ax network using SimEvents®, Stateflow®, and WLAN Toolbox™. The system-level model presented in this example includes functionalities such as configuring the priority of the traffic at the application layer, capability to generate and decode waveforms of Non-HT, HT-MF, VHT, HE-SU and HE-EXT-SU formats, MPDU aggregation and enabling block acknowledgment of MPDUs. The application layer throughput calculated using this model is validated against published calibration results from the TGax Task Group [ 4 ] for Box 3 scenarios (Tests 1a, 1b, and 2a) specified in TGax evaluation methodology [ 3 ]. The obtained application layer throughput is within the range of minimum and maximum throughput specified in published calibration results [ 4 ].


COMPONENT: wlan
EXAMPLENAME: HERFTransmitterExample
EXAMPLETITLE: Modeling and Testing an 802.11ax RF Transmitter
PRODUCT: MATLAB;WLAN Toolbox;RF Blockset;Simulink
DESCRIPTION:
Characterize the impact of RF impairments in an 802.11ax transmitter. The example generates a baseband IEEE® 802.11ax™ waveform by using WLAN Toolbox™ and models the RF transmitter by using RF Blockset™.


COMPONENT: wlan_phased
EXAMPLENAME: DMGSCLinkWithRFBeamformingExample
EXAMPLETITLE: 802.11ad Single Carrier Link with RF Beamforming in Simulink
PRODUCT: MATLAB;WLAN Toolbox;Simulink;Phased Array System Toolbox;RF Blockset
DESCRIPTION:
Model an IEEE 802.11ad™ single carrier link in Simulink® which includes a phased array antenna with RF beamforming. This example requires the following products:


COMPONENT: xilinxsoc
EXAMPLENAME: RFDataRecordingPlaybackforRFSoCDevicesExample
EXAMPLETITLE: RF Data Recording and Playback for RFSoC Devices
PRODUCT: MATLAB
DESCRIPTION:
Capture real-world RF data from RFSoC devices, and then use this data in MATLAB and Simulink for simulation and analysis.


COMPONENT: xilinxsoc
EXAMPLENAME: ReceiveToneWithDDRUsingRefDesignWFOnXilinxRFSoCDeviceExample
EXAMPLETITLE: Receive Tone with DDR4 Using Reference Design Workflow on Xilinx RFSoC Device
PRODUCT: MATLAB;DSP System Toolbox;SoC Blockset;HDL Coder
DESCRIPTION:
Design, simulate, and deploy algorithm to write and read captured RF samples from external DDR4 memory on Xilinx RFSoC device.


COMPONENT: xilinxsoc
EXAMPLENAME: MulticoreImplementationOfPulseDopplerRadarExample
EXAMPLETITLE: Multicore Implementation of Pulse-Doppler Radar
PRODUCT: MATLAB;DSP HDL Toolbox;SoC Blockset;Simulink
DESCRIPTION:
Implement a pulse-Doppler radar system using multiple processor cores on the Xilinx® Zynq® UltraScale+™ RFSoC evaluation kit. The example builds upon Pulse-Doppler Radar Using Xilinx RFSoC Device that uses a single processor core.


COMPONENT: xilinxzynq7000
EXAMPLENAME: GettingStartedWithTargetingXilinxVersalACAPPlatformExample
EXAMPLETITLE: Getting Started with Targeting Xilinx Versal Adaptive SoC Platform
PRODUCT: MATLAB;HDL Coder;Simulink
DESCRIPTION:
Use HDL Coder™ and the hardware-software co-design workflow to blink LEDs at various frequencies on the Xilinx® Versal® Adaptive SoC platform.


COMPONENT: xilinxzynq7000ec
EXAMPLENAME: CommFPGAIPCoreOnTheXilinxZynqPlatformUsingAXI4LiteExample
EXAMPLETITLE: Communicate with the Programmable Logic IP Core on Xilinx Zynq Platform Using AXI4-Lite Protocol
PRODUCT: MATLAB;Embedded Coder;Simulink
DESCRIPTION:
Communicate with the programmable logic IP core on Xilinx® Zynq® platform by using the Advanced eXtensible Interface 4 Lite (AXI4®-Lite) protocol.


COMPONENT: xilinxzynq7000ec
EXAMPLENAME: GettingStartedWithVxWorks7OnXilinxZynqPlatformExample
EXAMPLETITLE: Getting Started with VxWorks 7 on Xilinx Zynq Platform
PRODUCT: MATLAB;Embedded Coder;Simulink
DESCRIPTION:
Generate and run code from a Simulink® model onto a Xilinx® Zynq® ZC702 evaluation kit with a VxWorks® 7 operating system.


COMPONENT: xilinxzynq7000ec
EXAMPLENAME: PILVerificationOfSimulinkModelsExample
EXAMPLETITLE: Processor-in-the-Loop Verification of Simulink Models
PRODUCT: MATLAB;Simulink;Embedded Coder
DESCRIPTION:
Use Embedded Coder® Support Package for Xilinx® Zynq® Platforms to verify code using PIL simulation.


COMPONENT: xilinxzynq7000ec
EXAMPLENAME: CommunicatingWithXilinxZynqPlatformUsingUDPProtocolExample
EXAMPLETITLE: Communicate with Xilinx Zynq Platform Using UDP Protocol
PRODUCT: MATLAB;Embedded Coder;Simulink
DESCRIPTION:
Send data from a Simulink® model running on an ARM® Cortex®-A9 processor in a Xilinx® Zynq® platform to another model running on the host computer by using the UDP ethernet protocol.


COMPONENT: xilinxzynq7000ec
EXAMPLENAME: ECXilinxZynqRealTimeCodeExecutionProfilingExample
EXAMPLETITLE: Real-Time Code Execution Profiling
PRODUCT: MATLAB;Embedded Coder;Simulink
DESCRIPTION:
Profile the real-time execution of generated code running as an executable on the ARM® processor in a Xilinx® Zynq® platform.


COMPONENT: xilinxzynqbasedradio
EXAMPLENAME: ReceiveDataOnMultipleChannelsUsingSimulinkBlockExample
EXAMPLETITLE: Receive Data on Multiple Channels Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to receive data on two channels. The Channel mapping parameter of the AD936x Receiver block is set to [1 2] . The overflow port is disabled by clearing the Enable output port for overflow indicator parameter. The output data type is set to double. When you run this model, the connected Spectrum Analyzer blocks display the data noise received from the air through each channel. To generate an output tone, explore the Loopback parameter options on the Advanced tab. To generate a sine wave, set the Test signal injection parameter to Tone Inject Rx and the Signal generator mode to Tone . These settings apply to both channels.


COMPONENT: xilinxzynqbasedradio
EXAMPLENAME: TransmitDataOnSingleChannelUsingSimulinkBlockExample
EXAMPLETITLE: Transmit Data on Single Channel Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to transmit data on a single channel. The Channel mapping parameter of the AD936x Transmitter block is set to 1 . The underflow port is disabled by clearing the Enable output port for underflow indicator parameter. The Sine Wave block is configured to generate a 1 kHz sine wave, sampled at 1 MHz. When you run this model, the AD936x Transmitter block sends the generated sine wave through the air. You can inspect the generated data in the Spectrum Analyzer.


COMPONENT: xilinxzynqbasedradio
EXAMPLENAME: ReceiveDataOnSingleChannelUsingSimulinkBlockExample
EXAMPLETITLE: Receive Data on Single Channel Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to receive data on a single channel. The Channel mapping parameter of the AD936x Receiver block is set to 1 . The overflow port is disabled by clearing the Enable output port for overflow indicator parameter. The output data type is set to double. When you run this model, the connected Spectrum Analyzer displays the data noise received through the air. To generate an output tone, explore the Loopback parameter options on the Advanced tab. To generate a sine wave, set the Test signal injection parameter to Tone Inject Rx and the Signal generator mode to Tone .


COMPONENT: xilinxzynqbasedradio
EXAMPLENAME: TransmitDataOnMultipleChannelsUsingSimulinkBlockExample
EXAMPLETITLE: Transmit Data on Multiple Channels Using Simulink Block
PRODUCT: MATLAB;Simulink
DESCRIPTION:
This model is set up to transmit data on two channels. The Channel mapping parameter of the AD936x Transmitter block is set to [1 2] . The underflow port is disabled by clearing the Enable output port for underflow indicator parameter. The Sine Wave Channel 1 block is configured to generate an 8 kHz sine wave. The Sine Wave Channel 2 block is configured to generate a 1 kHz sine wave. Both sine waves are sampled at 1 MHz. When you run this model, the AD936x Transmitter block sends the generated and combined sine waves through the air. You can inspect the generated data in the Spectrum Analyzer blocks.


COMPONENT: xilinxzynqbasedvision
EXAMPLENAME: CornerWithZynqBasedHWAndMIPIExample
EXAMPLETITLE: Corner Detection with Zynq-Based Hardware and MIPI Sensor
PRODUCT: MATLAB;Simulink;Embedded Coder;HDL Coder;Computer Vision Toolbox;Vision HDL Toolbox
DESCRIPTION:
Target corner detection algorithm to the Zynq® hardware with MIPI® interface using the SoC Blockset™ Support Package for Xilinx® Devices.


