Adaptive filters with nonlinear RLS algorithm in impulse noise

被引：0

作者：

Leung, SH ^{[1
]}

Weng, JF ^{[1
]}

机构：

[1] City Univ Hong Kong, Dept Elect Engn, 83 Tat Chee Ave, Yau Yat Chuen, Peoples R China

来源：

ISCAS '99: PROCEEDINGS OF THE 1999 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL 3: ANALOG AND DIGITAL SIGNAL PROCESSING | 1999年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Adaptive filter using nonlinear recursive least square (RLS) algorithm in impulse noise is presented. Its mean and mean square behaviors are studied for Gaussian input signal and the class A impulse noise. Necessary and sufficient conditions for the stability of the algorithm are derived. A class of nonlinear functions including the linear one, which can be incorporated into RLS for assuring stable learning, is introduced. By simulations it is shown that the nonlinear algorithm not only provides convergence rate as fast as and also has excess mean squared error smaller than the linear counterpart in impulse noise.

引用

页码：37 / 40

页数：4

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