Blind nonlinear system identification based on a constrained hybrid genetic algorithm

被引：12

作者：

Chen, YW ^{[1
]}

Narieda, S

Yamashita, K

机构：

[1] Univ Ryukyus, Fac Engn, Okinawa, Japan

[2] Ocean Univ China, Inst Computat Sci & Engn, Shandong, Peoples R China

[3] Univ Osaka Prefecture, Coll Engn, Osaka, Japan

来源：

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 2003年 / 52卷 / 03期

关键词：

additive Gaussian noise; blind system identification; constraint; higher order cumulants (HOCs); hybrid genetic algorithm (GA); nonlinear system;

D O I：

10.1109/TIM.2003.814354

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：

System identification is an important issue in communication, instrumentation, and control systems. In this paper, we proposed a method with higher-order cumulant fitting for nonlinear system identification.. Compared with the conventional method, which uses second-order cumulant as a constraint, the proposed method uses fourth-order cumulant in order to smooth out the additive Gaussian noise. Since the cost function with higher-order statistics has local minima, we also propose to use a hybrid method of simplex and genetic algorithms to minimize the cost function. The applicability of the proposed method is demonstrated by the computer simulations.

引用

页码：898 / 902

页数：5