Identifying chaotic systems using wiener and hammerstein cascade models

Mathematical and Computer Modelling

Volumn 33, Issue 4-5, 2001, Pages 483-493

  Xu, Ming ^a   Chen, Guanrong ^b   Tian, Yan Tao ^a  

^a JILIN UNIVERSITY   (China)

^b UNIVERSITY OF HOUSTON   (United States)

Author keywords

Attractor; Chaos; Identification; Neural network; Time series

Indexed keywords

EID: 0035143087     PISSN: 08957177     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0895-7177(00)00256-9     Document Type: Article

References (20)

1. From chaos to order - Perspectives and methodologies in controlling chaotic nonlinear dynamical systems
2. Taming chaos: Part I, Synchronization, Part II, Control
3. An overview of bifurcation, chaos and nonlinear dynamics in control system
4. On feedback control of chaotic nonlinear dynamical systems
5. Making a dynamical system chaotic: Feedback control of Lyapunov exponents for discrete-time dynamical system
6. Using small perturbations to control chaos
7. System identification and model-based control of a chaotic system
8. Synchronizing chaotic circuits
9. Identification and control of chaotic system: An artificial neural network approach
10. Identifying chaotic system via a Wiener-type cascade model
11. Controlling chaos with a neural network
12. Neural-network based adaptive control of uncertain chaotic system
13. Neural networks reconstruction and prediction of chaotic dynamics
14. Identification and control of dynamical system using neural networks
15. Nonparametric identification of Wiener systems by orthogonal series
16. Identification of nonlinear biological systems: Wiener and Hammerstein models