Identifying chaotic systems using Wiener and Hammerstein cascade models

Citation
M. Xu et al., Identifying chaotic systems using Wiener and Hammerstein cascade models, MATH COMP M, 33(4-5), 2001, pp. 483-493
Citations number
20
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Engineering Mathematics
Journal title
MATHEMATICAL AND COMPUTER MODELLING
ISSN journal
0895-7177 → ACNP
Volume
33
Issue
4-5
Year of publication
2001
Pages
483 - 493
Database
ISI
SICI code
0895-7177(200102/03)33:4-5<483:ICSUWA>2.0.ZU;2-M
Abstract
This paper describes two basic structures for identifying chaotic systems b ased on the Wiener and Hammerstein cascade models, in which three-layer fee dforward artificial neural network is employed as the nonlinear static subs ystem and a simple linear plant is used as the dynamic subsystem. Through t raining of the neural network and choosing an appropriate linear subsystem, various chaotic systems can be well identified by these two basic structur es. Computer simulation results on Henon and Lozi systems are presented to demonstrate the effectiveness of these proposed structures. It is also show n that two chaotic systems whose outputs are different can actually exhibit similar chaotic attractors. (C) 2001 Elsevier Science Ltd. All rights rese rved.