Switching criterion for sub-and super-Gaussian additive noise in adaptive filtering

被引：19

作者：

Wang, Gang ^{[1
]}

Xue, Rui ^{[2
]}

Zhao, Ji ^{[3
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Ctr Robot, Chengdu 611731, Sichuan, Peoples R China

[2] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China

[3] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China

来源：

SIGNAL PROCESSING | 2018年 / 150卷

基金：

中国国家自然科学基金;

关键词：

Adaptive filter; Least mean square; Maximum correntropy criterion; Least mean fourth; Normalized kurtosis; MEAN 4TH ALGORITHM; MAXIMUM CORRENTROPY CRITERION; PERFORMANCE ANALYSIS; CONVERGENCE; NETWORKS; ERROR;

D O I：

10.1016/j.sigpro.2018.04.017

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：

Additive noise distributions can be divided into three types: Gaussian, super-and sub-Gaussian. The existing algorithms for adaptive filtering do not provide a better performance than the least mean square (LMS) method for the super-and sub-Gaussian noise simultaneously. For example, the maximum corren-tropy criterion performs better (worse) than the LMS method for super-Gaussian (sub-Gaussian) noise, whereas the least mean fourth performs better (worse) than the LMS method for sub-Gaussian (super-Gaussian) noise. We propose a criterion for switching between sub-and super-Gaussian additive noise, that could be used to assess whether the error signal had a sub-or super-Gaussian profile, and thus determine which algorithm would work best in the iterative process. Simulations demonstrate that the switching criterion helps the proposed switching algorithm to produce a better performance than the LMS algorithm for sub and super-Gaussian noise simultaneously. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：166 / 170

页数：5

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