nwpredmodel class

Predictor model class, which specifies the mapping from nodes and excitations of a network structure to inputs and outputs of a predictor model. An instance of this class is required for single module identification, where a subset of the excitation and node signals from the full network are required for the estimation of the target module.

Construction

• pred = nwpredmodel(networkStructure)  creates a full network identification predictor model based on the topology in the provided LabelledAdjStruct argument.
• pred = nwpredmodel(networkStructure,target,Rset,Dset,Yset)  creates a single module identification predictor model based on the topology in the provided LabelledAdjStruct argument, and the provided target, input excitations (Rset), input nodes (Dset) and output nodes (Yset).
• pred = nwpredmodel(path)  creates a predictor model object from file, previously stored using the save method.
• pred = nwpredmodel(__,Name=Value)  creates a predictor model with additional properties set according to the provided values. Currently, the type, NoiseCovariance and Report properties cannot be set in this way.

Properties

• Name

  character array	string

  Name of predictor model. Empty by default.

• NetworkStructure

  Structure array

  Details of the network structure from which the predictor model is generated. When set either during construction or after, this structure must be provided as a LabelledAdjStruct object. The object is then converted to a structure array. Modifying fields of this structure array directly is currently not supported.

• type

  string

  Type of the predictor model. Defaults to 'tf'.

• target

  [:,2] array

  Target module for identification, specified by the indices of the input and output nodes in the network structure. Similar to targetLabelNr, but here the set of integers refers to the position of the nodes in the network structure, rather than the node numbers. For example, when NetworkStructure.NodeNumbers = [1 3 2 4] and targetLabelNr = [1 2], then target = [1 3].

• Rset

  $[1,n_{R}]$ array

  Indices of input excitations in the predictor model. Similar to RsetLabelNr, but here the set of integers refers to the position of the excitations in the network structure, rather than the excitation numbers. For example, when NetworkStructure.ExcitationNumbers = [1 3 2 4] and RsetLabelNr = [1 2], then Rset = [1 3].

• Dset

  $[1,n_{D}]$ array

  Indices of input nodes in the predictor model. Similar to DsetLabelNr, but here the set of integers refers to the position of the nodes in the network structure, rather than the node numbers. For example, when NetworkStructure.NodeNumbers = [1 3 2 4] and DsetLabelNr = [1 2], then Dset = [1 3].

• Yset

  $[1,n_{Y}]$ array

  Indices of output nodes in the predictor model. Similar to YsetLabelNr, but here the set of integers refers to the position of the nodes in the network structure, rather than the node numbers. For example, when NetworkStructure.NodeNumbers = [1 3 2 4] and YsetLabelNr = [1 2], then Yset = [1 3].

• targetLabelNr

  [:,2] integer array

  Target module for identification, specified by the label numbers of the input and output nodes in the network structure (corresponding to NetworkStructure.NodeNumbers). An empty ([0,2]) array indicates the full network should be identified. Defaults to an empty array.

• RsetLabelNr

  $[1,n_{R}]$ integer array

  Label numbers of input excitations in the predictor model, corresponding to NetworkStructure.ExcitationNumbers. For a full network predictor model, all excitations in the NetworkStructure property appear in the input. For a single module predictor model, this property defaults to an empty array.

• DsetLabelNr

  $[1,n_{D}]$ integer array

  Numbers of input nodes in the predictor model, corresponding to NetworkStructure.NodeNumbers. For a full network predictor model, all nodes in the NetworkStructure property appear in the output. For a single module predictor model, this property defaults to an empty array.

• YsetLabelNr

  $[1,n_{Y}]$ integer array

  Numbers of output nodes in the predictor model, corresponding to NetworkStructure.NodeNumbers. For a full network predictor model, all nodes in the NetworkStructure property appear in the output. For a single module predictor model, this property defaults to an empty array.

• G

  PredictorMap object

  Structural and estimation properties of the mapping from input nodes to output nodes.

• T

  PredictorMap object

  Structural and estimation properties of the mapping from excitations to output nodes.

• H

  PredictorMap object

  Structural and estimation properties of the mapping from noise signals to output nodes.

• order

  positive scalar

  Initial order of the transfer functions in G, T and H. Note that this order can be superseded by modifying the $G$, $T$ and $H$ properties.

• NoiseCovariance

  $[n_{E},n_{E}]$ double array

  Estimated noise covariance matrix.

• Report

  nwreport object

  Estimation report, containing e.g. information on data used, fit and estimation method used.

• nodesW

  struct

  Structure specifying the indices of the input and output nodes in the predictor model, with the fields:

  • Y (nodes appearing in output)
  • D (nodes appearing in input)
  • Q (nodes appearing in both input and output)
  • O (nodes appearing only in output)
  • U (nodes appearing only in input)

• nodesR

  $[n_{R},1]$ array

  Indices of excitations appearing in the predictor model.

• idmodule

  tf object

  Transfer function representation of the (to be) identified module. Retrieved by indexing the G property with the indices specified in the target property.

• nD

  positive scalar

  Number of input nodes.

• nY

  positive scalar

  Number of output nodes.

• nR

  positive scalar

  Number of excitation signals.

• nE

  positive scalar

  Number of noise signals.

• nU

  positive scalar

  Total number of inputs.

• full

  logical scalar

  Indicates if the predictor model specifies full network identification.

• struc

  LabelledAdjStruct object

  Shorthand for NetworkStructure

Methods

• save

  Save properties of the object.

  Syntax

  • save(pred,path)  stores a struct containing the properties of the predictor model object at the location specified by path.

  Input arguments

  • pred

    nwpredmodel object

  • path

    character array	string

    Path to folder in which the predictor model details should be stored.

• get

  Displays the properties of the object.

  Syntax

  • get(pred)  displays a struct containing the properties of the nwpredmodel object.

  Input arguments

  • pred

    nwpredmodel object