Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator |
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| Institution: | 1. School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment, Nanjing 210044, Jiangsu Province, China\n;3. School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China;1. Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing 100044, PR China;2. Department of Mathematics, School of Science, Hebei University of Science and Technology, Shijiazhuang, Hebei Province 050000, PR China;1. Department of Physics, Lanzhou University of Technology, Lanzhou 730050 China;2. NAAM-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia;3. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China |
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| Abstract: | 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. |
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