Decomposition-Based Recursive Least Squares Algorithm for Wiener Nonlinear Feedback FIR-MA Systems Using the Filtering Theory

被引：3

作者：

Wang, Ziyun ^{[1
]}

Wang, Yan ^{[1
]}

Ji, Zhicheng ^{[1
]}

机构：

[1] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2014年 / 33卷 / 11期

基金：

中国国家自然科学基金;

关键词：

System identification; Wiener model; Recursive least squares algorithms; Filtering theory; Key-term decomposition; PARAMETER-ESTIMATION; ITERATIVE ALGORITHMS; IDENTIFICATION; MODEL;

D O I：

10.1007/s00034-014-9806-5

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A decomposition-based recursive least squares algorithm is developed for Wiener nonlinear systems described by finite impulse response moving average models. After transferring a finite impulse response moving average (FIR-MA) model to a controlled autoregressive model, we compute the parameters by combining the decomposition principle and the least squares method and using the filtering idea. The simulation results validate the proposed algorithm.

引用

页码：3649 / 3662

页数：14

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