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nwidfullSLS function

Identify a full network using the Sequential Least Squares (SLS) algorithm.


  • model = nwidfullSLS(data,model,orders,options)  performs full network identification based on the provided data, initialized network model, model orders and option set. The identified network model is returned.

Input arguments

  • data

    nwdata object

    Network data object. All input excitation, input node and output node signals (as referred to by their labels) of the network structure in the predictor model must be present in the data.

  • model

    nwmodel object

    Initialized network model object. For each element, whether or not it is fixed, parameter values of fixed elements and parameter initializations can be set using the G, T and H fields (PredictorMap objects). Setting delay terms and orders for each element separately is currently not supported. All modules are assumed to be strictly proper, and a global model order is used.

  • order

    positive integer

    Order of estimated transfer functions in G, T and H.

  • options

    nwidfullSLSOptions object

    Option set for nwidfullSLS function. Can be constructed using options = nwidfullSLSOptions for the default option set or options = nwidfullSLSOptions(Name=Value,...) to set specified options.

Output arguments

  • model

    nwmodel object

    Estimated network model object. The G, T and H fields are populated with the estimated and fixed parameters. The NoiseCovariance property stores the estimated noise covariance.Details of the estimation are stored in the Report property.