Robust Recursive Least-Squares Adaptive-Filtering Algorithm for Impulsive-Noise Environments

被引：42
|
作者：
Bhotto, Md. Zulfiquar Ali [1 ]
Antoniou, Andreas [1 ]
机构：
[1] Univ Victoria, Dept Elect & Comp Engn, Victoria, BC V8W 3P6, Canada
来源：
IEEE SIGNAL PROCESSING LETTERS | 2011年 / 18卷 / 03期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Adaptive filters; RLS adaptation algorithms; robust adaptation algorithms;
D O I：
10.1109/LSP.2011.2106119
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 new robust recursive least-squares (RLS) adaptive filtering algorithm that uses a priori error-dependent weights is proposed. Robustness against impulsive noise is achieved by choosing the weights on the basis of the norms of the crosscorrelation vector and the input-signal autocorrelation matrix. The proposed algorithm also uses a variable forgetting factor that leads to fast tracking. Simulation results show that the proposed algorithm offers improved robustness as well as better tracking compared to the conventional RLS and recursive least-M estimate adaptation algorithms.
引用
收藏
页码：185 / 188
页数：4
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