Performance Analysis of Adaptive Filters for Time-Varying Systems

被引：0
|
作者：
Yu Xia [1 ]
Liu Jianchang [1 ,2 ]
Li Hongru [1 ,2 ]
机构：
[1] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110819, Peoples R China
来源：
2013 32ND CHINESE CONTROL CONFERENCE (CCC) | 2013年
关键词：
Adaptive filtering; time-varying systems; LMS filter; RLS filter; LEAST-SQUARES ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Two typical adaptive algorithms, LMS filtering and RLS filtering, were introduced and compared in this paper. The convergence performance and tracking performance in non-stationary were analyzed by simulation. When the identification plant was time-varying, adaptive filters should have the ability of tracking the minimum point. Compared with LMS filters, one important feature RLS filters have is convergence rate, but the improvement of this performance is cost by the increasing calculation complexity of RLS filters. According to simulation analysis, in time-varying environment, LMS filters have better tracking performance than RLS filters.
引用
收藏
页码：8572 / 8575
页数：4
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