This paper addresses the problem of recursive identification of Wiener nonlinear systems whose linear subsystems are observable state-space models. The maximum likelihood principle and the recursive identification technique are employed to develop a recursive maximum likelihood identification algorithm which estimates the unknown parameters and the system states interactively. In comparison with the developed recursive maximum likelihood algorithm, a recursive generalized least squares algorithm is also proposed for identification of such Wiener systems. The performance of the developed algorithms is validated by two illustrative examples.

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recursive identification of wiener nonlinear systems algorithms linear recursive generalized least squares algorithm recursive maximum likelihood identification algorithm

Liang Hua,Juping Gu,Junhong Li,Wei Xing Zheng,.A Recursive Identification Algorithm for Wiener Nonlinear Systems with Linear State-Space Subsystem. 37 (6),2374–2393.

Liang Hua, et al."A Recursive Identification Algorithm for Wiener Nonlinear Systems with Linear State-Space Subsystem" 37

Liang Hua,Juping Gu,Junhong Li,Wei Xing Zheng,"A Recursive Identification Algorithm for Wiener Nonlinear Systems with Linear State-Space Subsystem"