For this example, consider sparseFOContinuous.mat which contains sparse matrices for a continuous-time sparse first-order state-space model.

Extract the sparse matrices from sparseFOContinuous.mat.

load('sparseFOContinuous.mat','A','B','C','D','E');

Create the sparss model object.

sys = sparss(A,B,C,D,E)

The output sys is a continuous-time sparss model object containing with 199 states, 1 input and 1 output.

You can use the spy command to visualize the sparsity of the sparss model object.

spy(sys)

For this example, consider sparseFODiscrete.mat which contains sparse matrices for a discrete-time sparse first-order state-space model.

Extract the sparse matrices from sparseFODiscrete.mat.

load('sparseFODiscrete.mat','A','B','C','D','E','ts');

Create the sparss model object.

sys = sparss(A,B,C,D,E,ts)

Sparse discrete-time state-space model with 1 outputs, 1 inputs, and 398 states.

Use "spy" and "showStateInfo" to inspect model structure. 
Type "properties('sparss')" for a list of model properties. 
Type "help sparssOptions" for available solver options for this model.

The output sys is a discrete-time sparss model object containing with 398 states, 1 input and 1 output.

You can use the spy command to visualize the sparsity of the sparss model object.

spy(sys)

You can also view model properties of the sparss model object.

properties('sparss')

Properties for class sparss:

    A
    B
    C
    D
    E
    Scaled
    StateInfo
    SolverOptions
    InternalDelay
    InputDelay
    OutputDelay
    Ts
    TimeUnit
    InputName
    InputUnit
    InputGroup
    OutputName
    OutputUnit
    OutputGroup
    Notes
    UserData
    Name
    SamplingGrid