Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator
| Autor: | Yi Jiang, Yibo Zhao, Jiuchao Feng, Lifu Wu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Polynomial
General Mathematics Applied Mathematics General Physics and Astronomy Statistical and Nonlinear Physics Memristor 01 natural sciences Chaos theory 010305 fluids & plasmas law.invention Adaptive filter Nonlinear system Control theory law Control system Adaptive system 0103 physical sciences Convergence (routing) 010301 acoustics Mathematics |
| Zdroj: | Chaos, Solitons & Fractals. 87:12-16 |
| ISSN: | 0960-0779 |
| DOI: | 10.1016/j.chaos.2016.03.004 |
| Popis: | Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error. |
| Databáze: | OpenAIRE |
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