nwidfullSLS function
Identify a full network using the Sequential Least Squares (SLS) algorithm.
Syntax
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
objectNetwork 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
objectInitialized 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
andH
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
andH
.options
nwidfullSLSOptions
objectOption set for
nwidfullSLS
function. Can be constructed usingoptions = nwidfullSLSOptions
for the default option set oroptions = nwidfullSLSOptions(Name=Value,...)
to set specified options.
Output arguments
model
nwmodel
objectEstimated network model object. The
G
,T
andH
fields are populated with the estimated and fixed parameters. TheNoiseCovariance
property stores the estimated noise covariance.Details of the estimation are stored in theReport
property.