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Download MATLAB SYSTEM IDENTIFICATION TOOLBOX 7 User`s guide
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Supported Nonlinearity Estimators Supported Nonlinearity Estimators In this section... “Types of Nonlinearity Estimators” on page 4-25 “Creating Custom Nonlinearities” on page 4-26 Types of Nonlinearity Estimators When configuring the nonlinear ARX and Hammerstein-Wiener models for estimation, you must specify a mathematical structure for the nonlinear portion of the model. If you are working in the System Identification Tool GUI, specify the nonlinearity type by name when you configure the nonlinear model structure. If you are estimating or constructing a nonlinear model at the command line instead, specify the nonlinearity as an argument in the nlarx or nlhw estimation command. The following table summarizes supported nonlinearities in the System Identification Toolbox product for each type of nonlinear model. For a description of each nonlinearity, see the references page for the corresponding nonlinearity object. Nonlinearity Object Name Supported Model Type Supports Multiple Inputs? Custom Network (user-defined) customnet Hammerstein-Wiener and Nonlinear ARX Yes Dead Zone deadzone Hammerstein-Wiener No Neural Network neuralnet Nonlinear ARX Yes Piecewise Linear pwlinear Hammerstein-Wiener No One-Dimensional Polynomial poly1d Hammerstein-Wiener No Saturation saturation Hammerstein-Wiener No Sigmoid Network sigmoidnet Hammerstein-Wiener and Nonlinear ARX Yes 4-25
