Diffusion normalized Huber adaptive filtering algorithm

被引：31

作者：

Li, Zhi ^{[1
]}

Guan, Sihai ^{[1
]}

机构：

[1] Xidian Univ, Sch Electromech Engn, 2 South Taibai Rd, Xian 710071, Shaanxi, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2018年 / 355卷 / 08期

基金：

中国国家自然科学基金;

关键词：

LEAST-MEAN SQUARES; DISTRIBUTED ESTIMATION; STEP-SIZE; FORMULATION;

D O I：

10.1016/j.jfranklin.2018.03.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we propose an adapt-then-combine (ATC) diffusion normalized Huber adaptive filtering (ATC-DNHuber) algorithm for distributed estimation in impulsive interference environments. Firstly, a normalized Huber adaptive filter (NHuber) is developed to reduce the effect of the eigenvalue spread of the input signal. Then we extend the NHuber to develop an ATC diffusion algorithm by applying the NHuber algorithm at all agents. In addition, the mean stability performance and computational complexity are analyzed theoretically. In addition, Furthermore, simulation results demonstrate that the ATC-DNHuber algorithm can perform better in identifying the unknown coefficients under the complex and changeable impulsive interference environments. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：3812 / 3825

页数：14

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