An Improved Diffusion Affine Projection Estimation Algorithm for Wireless Sensor Networks

被引：4

作者：

Hu, Limei ^{[1
,2
,3
,4
]}

Chen, Feng ^{[1
,2
,3
,4
]}

Duan, Shukai ^{[1
]}

Wang, Lidan ^{[2
,3
]}

Wu, Jiagui ^{[2
]}

机构：

[1] Southwest Univ, Coll Artificial Intelligence, Chongqing 400715, Peoples R China

[2] Southwest Univ, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China

[3] Southwest Univ, Brain Inspired Comp & Intelligent Control Key Lab, Chongqing 400715, Peoples R China

[4] Chongqing Collaborat Innovat Ctr Brain Sci, Chongqing 400715, Peoples R China

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2020年 / 39卷 / 06期

基金：

中国国家自然科学基金; 国家重点研发计划;

关键词：

Wireless sensor networks; Parameter estimation; Diffusion strategy; Potential risk; Adaptive node selecting; RECURSIVE LEAST-SQUARES; DISTRIBUTED ESTIMATION; LMS ALGORITHM; MEAN SQUARES; STRATEGIES; OPTIMIZATION; FORMULATION; AGENTS;

D O I：

10.1007/s00034-019-01317-5

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：

Affine projection algorithms have shown robustness against highly correlated input signals. To make the affine projection algorithm applicable for parameter estimation in wireless sensor networks, this work proposed a novel distributed affine projection algorithm by using the adapt-then-combine (ATC) scheme of the diffusion strategy. However, poorly performing nodes can potentially degrade to estimation performance. Thus, we develop an improved ATC diffusion affine projection algorithm (improved ATC-dAPA) with adaptive node selection to maintain the estimation accuracy. The mean and mean square deviation of the proposed algorithm are analyzed. The numerical simulation results illustrate that the proposed algorithm can achieve more accurate estimations than several related algorithms.

引用

页码：3173 / 3188

页数：16

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