Gradient-Based Iterative Identification for Wiener Nonlinear Dynamic Systems with Moving Average Noises

被引：5
作者：
Zhou, Lincheng [1 ]
Li, Xiangli [1 ]
Xu, Huigang [1 ]
Zhu, Peiyi [1 ]
机构：
[1] Changshu Inst Technol, Sch Elect & Automat Engn, Hushan Rd 99, Changshu 215500, Peoples R China
来源：
ALGORITHMS | 2015年 / 8卷 / 03期
关键词：
nonlinear dynamic system; stochastic gradient; iterative algorithm; output error moving average; parameter estimation;
D O I：
10.3390/a8030712
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper focuses on the parameter identification problem for Wiener nonlinear dynamic systems with moving average noises. In order to improve the convergence rate, the gradient-based iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates, and to compute iteratively the noise estimates based on the obtained parameter estimates. The simulation results show that the proposed algorithm can effectively estimate the parameters of Wiener systems with moving average noises.
引用
收藏
页码：712 / 722
页数：11
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