Normalized least mean-square algorithm with variable step size based on diffusion strategy

Sheng Zhang; Wei Xing Zheng

doi:10.1109/ISCAS.2018.8351517

Normalized least mean-square algorithm with variable step size based on diffusion strategy

Sheng Zhang, Wei Xing Zheng

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

9 Citations (Scopus)

Abstract

![CDATA[In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffusion normalized least mean-square (DifNLMS) algorithm is developed to tackle the considered problem. The main idea of the developed variable multi-step-size DifNLMS (VMSSDifNLMS) algorithm is to assign an individual time-varying step-size for each delivered signal in the weight adaptation step. As such, the developed algorithm is able to achieve a good tradeoff between fast convergence rate and low misadjustment. Numerical simulations are presented to show that the VMSSDifNLMS algorithm outperforms the conventional DifNLMS, VSSDifLMS, and DifLMS with optimal adaptive combination in terms of both convergence rate and steady-state error.]]

Original language	English
Title of host publication	2018 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings, 27Ã¢€“30 May 2018, Florence, Italy
Publisher	IEEE
Number of pages	4
ISBN (Print)	9781538648810
DOIs	https://doi.org/10.1109/ISCAS.2018.8351517
Publication status	Published - 2018
Event	IEEE International Symposium on Circuits and Systems - Duration: 27 May 2018 → …

Publication series

Name
ISSN (Print)	2379-447X

Conference

Conference	IEEE International Symposium on Circuits and Systems
Period	27/05/18 → …

Keywords

automatic control
computer networks

Access to Document

10.1109/ISCAS.2018.8351517

Cite this

@inproceedings{f5b220a7722f4ee882f46f643cde9a3d,

title = "Normalized least mean-square algorithm with variable step size based on diffusion strategy",

abstract = "![CDATA[In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffusion normalized least mean-square (DifNLMS) algorithm is developed to tackle the considered problem. The main idea of the developed variable multi-step-size DifNLMS (VMSSDifNLMS) algorithm is to assign an individual time-varying step-size for each delivered signal in the weight adaptation step. As such, the developed algorithm is able to achieve a good tradeoff between fast convergence rate and low misadjustment. Numerical simulations are presented to show that the VMSSDifNLMS algorithm outperforms the conventional DifNLMS, VSSDifLMS, and DifLMS with optimal adaptive combination in terms of both convergence rate and steady-state error.]]",

keywords = "automatic control, computer networks",

author = "Sheng Zhang and Zheng, {Wei Xing}",

year = "2018",

doi = "10.1109/ISCAS.2018.8351517",

language = "English",

isbn = "9781538648810",

publisher = "IEEE",

booktitle = "2018 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings, 27{\~A}¢€“30 May 2018, Florence, Italy",

note = "IEEE International Symposium on Circuits and Systems ; Conference date: 27-05-2018",

}

TY - GEN

T1 - Normalized least mean-square algorithm with variable step size based on diffusion strategy

AU - Zhang, Sheng

AU - Zheng, Wei Xing

PY - 2018

Y1 - 2018

N2 - ![CDATA[In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffusion normalized least mean-square (DifNLMS) algorithm is developed to tackle the considered problem. The main idea of the developed variable multi-step-size DifNLMS (VMSSDifNLMS) algorithm is to assign an individual time-varying step-size for each delivered signal in the weight adaptation step. As such, the developed algorithm is able to achieve a good tradeoff between fast convergence rate and low misadjustment. Numerical simulations are presented to show that the VMSSDifNLMS algorithm outperforms the conventional DifNLMS, VSSDifLMS, and DifLMS with optimal adaptive combination in terms of both convergence rate and steady-state error.]]

AB - ![CDATA[In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffusion normalized least mean-square (DifNLMS) algorithm is developed to tackle the considered problem. The main idea of the developed variable multi-step-size DifNLMS (VMSSDifNLMS) algorithm is to assign an individual time-varying step-size for each delivered signal in the weight adaptation step. As such, the developed algorithm is able to achieve a good tradeoff between fast convergence rate and low misadjustment. Numerical simulations are presented to show that the VMSSDifNLMS algorithm outperforms the conventional DifNLMS, VSSDifLMS, and DifLMS with optimal adaptive combination in terms of both convergence rate and steady-state error.]]

KW - automatic control

KW - computer networks

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:46672

U2 - 10.1109/ISCAS.2018.8351517

DO - 10.1109/ISCAS.2018.8351517

M3 - Conference Paper

SN - 9781538648810

BT - 2018 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings, 27Ã¢€“30 May 2018, Florence, Italy

PB - IEEE

T2 - IEEE International Symposium on Circuits and Systems

Y2 - 27 May 2018

ER -

Normalized least mean-square algorithm with variable step size based on diffusion strategy

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