A recursive least M-estimate (RLM) adaptive filter for robust filtering in impulse noise

被引：85

作者：

Zou, Y ^{[1
]}

Chan, SC ^{[1
]}

Ng, TS ^{[1
]}

机构：

[1] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

IEEE SIGNAL PROCESSING LETTERS | 2000年 / 7卷 / 11期

关键词：

adaptive filter; impulse noise suppression; recursive least M-estimate algorithm; robust statistics; system identification;

D O I：

10.1109/97.873571

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：

This paper proposes a recursive least M-estimate (RLM) algorithm for robust adaptive filtering in impulse noise, It employs an M-estimate cost function, which is able to suppress the effect of impulses on the filter weights, Simulation results showed that the RLM algorithm performs better than the conventional RLS, NRLS, and the OSFKF algorithms when the desired and input signals are corrupted by impulses. Its initial convergence, steady-state error, computational complexity, and robustness to sudden system change are comparable to the conventional RLS algorithm in the presence of Gaussian noise alone.

引用

页码：324 / 326

页数：3