Identification of Wiener Models by Separable Least-Squares

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This paper is concerned with the identification of a discrete-time Wiener model, composed of a linear time-invariant (LTI) system and a static nonlinearity. Introducing a set of basis functions for the nonlinearity, we employ an output error criterion for the Wiener model identification. We apply the separable least-squares method to develop a two-stage method that identifies the LTI system using the data driven local coordinate (DDLC) and estimates coefficients of the nonlinearity by a simple substitution. Two examples are included.

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