A robust LMS adaptive algorithm over distributed networks

Muhammad O. Bin Saeed*, Azzedine Zerguine, Salam A. Zummo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

power estimates on the behavior of a noise constrained diffusion-based adaptive algorithm for distributed adaptive networks. For good performance, the noise constrained diffusion least mean square (NCDLMS) algorithm assumes knowledge of the noise variance is available at each node. In this work, it is shown that the NCDLMS algorithm is robust to large variations in noise variance estimation. Moreover, the mean and steady-state analyses of the NCDLMS algorithm are carried out and simulation results are found to corroborate the theoretical findings. Great improvement in performance is obtained through the use of the proposed algorithm even when no information on the noise variance is available. The increased computational complexity of the NCDLMS algorithm is justified through the performance improvement it offers.

Original languageEnglish
Title of host publicationConference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Pages547-550
Number of pages4
DOIs
StatePublished - 2011

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Keywords

  • Adaptive filters
  • Variable step-size least mean square
  • diffusion algorithm
  • noise constrained least mean square

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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