Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations

• Published in: Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference pp. 3632 - 3636
• Main Authors: Dongqing Wang, Yanyun Chu, Feng Ding
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2009
• Subjects: Convergence; Cost function; Educational institutions; Hammerstein models; Iterative algorithms; iterative identification; Iterative methods; least squares; Least squares approximation; Least squares methods; Nonlinear dynamical systems; Nonlinear systems; Parameter estimation; recursive identification; stochastic gradient; System modelling; Wiener models

This paper derives a least squares based and a gradient based iterative identification algorithms for Wiener nonlinear systems. These methods separate one bilinear-parameter cost function into two linear-parameter cost functions, estimating directly the parameters of the Wiener systems. The simulati...