Digital Filtering

Zero-phase filtering, median filtering, overlap-add filtering, transfer function representation

Lowpass, highpass, bandpass, and bandstop filter multichannel data without having to design filters or compensate for delays. Perform zero-phase filtering to remove delay and phase distortion. Use median or Hampel filtering to remove spikes and outliers. Convert transfer functions to different representations, such as second-order sections or poles and zeros.

Apps

Signal AnalyzerVisualize and compare multiple signals and spectra

Functions

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bandpassBandpass-filter signals
bandstopBandstop-filter signals
highpassHighpass-filter signals
lowpassLowpass-filter signals
fftfiltFFT-based FIR filtering using overlap-add method
filter1-D digital filter
filter22-D digital filter
filtfiltZero-phase digital filtering
filticInitial conditions for transposed direct-form II filter implementation
hampelOutlier removal using Hampel identifier
latcfiltLattice and lattice-ladder filter implementation
medfilt11-D median filtering
residuezZ-transform partial-fraction expansion
sgolayfiltSavitzky-Golay filtering
sosfiltSecond-order (biquadratic) IIR digital filtering
convConvolution and polynomial multiplication
conv22-D convolution
convmtxConvolution matrix
deconvDeconvolution and polynomial division
cell2sosConvert second-order sections cell array to matrix
eqtflengthEqualize lengths of transfer function numerator and denominator
latc2tfConvert lattice filter parameters to transfer function form
sos2cellConvert second-order sections matrix to cell array
sos2ssConvert digital filter second-order section parameters to state-space form
sos2tfConvert digital filter second-order section data to transfer function form
sos2zpConvert digital filter second-order section parameters to zero-pole-gain form
ssConvert digital filter to state-space representation
ss2sosConvert digital filter state-space parameters to second-order sections form
ss2tfConvert state-space representation to transfer function
ss2zpConvert state-space filter parameters to zero-pole-gain form
tfConvert digital filter to transfer function
tf2latcConvert transfer function filter parameters to lattice filter form
tf2sosConvert digital filter transfer function data to second-order sections form
tf2ssConvert transfer function filter parameters to state-space form
tf2zpConvert transfer function filter parameters to zero-pole-gain form
tf2zpkConvert transfer function filter parameters to zero-pole-gain form
zp2sosConvert zero-pole-gain filter parameters to second-order sections form
zp2ssConvert zero-pole-gain filter parameters to state-space form
zp2tfConvert zero-pole-gain filter parameters to transfer function form
zpkConvert digital filter to zero-pole-gain representation
dspfwizCreate Simulink filter block using Realize Model panel
filt2blockGenerate Simulink filter block

Topics

Filtering Data With Signal Processing Toolbox Software

Design and implement a filter using command-line functions or an interactive app.

Anti-Causal, Zero-Phase Filter Implementation

Eliminate the phase distortion introduced by an IIR filter.

Compensate for the Delay Introduced by an FIR Filter

Use indexing to counteract the time shifts introduced by filtering.

Compensate for the Delay Introduced by an IIR Filter

Remove delays and distortion introduced by filtering, when it is critical to keep phase information intact.

Speaker Crossover Filters

Devise a simple model of a digital three-way loudspeaker using Chebyshev Type I designs. Visualize the poles, zeros, and frequency responses of the filters.

Discrete-Time System Models

Explore different schemes to represent digital filters.

Linear System Transformations

Convert between various representational schemes for digital filters.

Human Activity Recognition Simulink Model for Smartphone Deployment (Statistics and Machine Learning Toolbox)

Generate code from a classification Simulink® model prepared for deployment to a smartphone.

Featured Examples