An Incremental Least-Mean Square Algorithm With Adaptive Combiner

被引：3

作者：

Tinati, Mohammad Ali ^{[1
]}

Rastegarnia, Amir ^{[1
]}

Khalili, Azam ^{[1
]}

机构：

[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran

来源：

ICWMMN 2010, PROCEEDINGS | 2010年

关键词：

adaptive filter; distributed estimation; least-mean square; incremental cooperation; STRATEGIES;

D O I：

10.1049/cp.2010.0667

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we propose a new incremental least-mean square (LMS) algorithm with adaptive combination strategy The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variation of signal-to-noise ratio (SNR) The performance of our algorithm is more remarkable in inhomogeneous environments when there are some noisy nodes (nodes with low SNR) in the network. The simulation results show that the proposed algorithm outperforms than the incremental LMS algorithm

引用

页码：266 / 269

页数：4

共 11 条

[1]

[Anonymous], 2006, AD SENS ARR PROC WOR

[2]

[Anonymous], P IEEE INT C AC SPEE

[3] Diffusion recursive least-squares for distributed estimation over adaptive networks [J].