Recursive identification for Wiener systems using Gaussian inputs |
| |
| Authors: | Xiao‐Li Hu Han‐Fu Chen |
| |
| Affiliation: | 1. Department of Mathematics, College of Sciences, China Jiliang University, Hangzhou 310018, China;2. Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China |
| |
| Abstract: | The recursive algorithms are given for identifying the single‐input single‐output Wiener system which consists of a moving average type linear subsystem followed by a static nonparametric nonlinearity. The input is defined to be a sequence of mutually independent Gaussian random variables. The estimates for coefficients of the linear subsystem as well as for f(v) at any v are proved to converge to the true values with probability one. A numerical example is given, justifying the theoretical analysis. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society |
| |
| Keywords: | Wiener system nonparametric nonlinearity recursive estimate strong consistency stochastic approximation |
|
|
