The leaky least mean mixed norm algorithm

Mohammed Abdul Nasar, Azzedine Zerguine

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

15 Scopus citations

Abstract

In this work, a leakage-based variant of the Least Mean Mixed Norm (LMMN) algorithm, the leaky Least Mean Mixed Norm (LLMMN) algorithm, is derived. The proposed algorithm will help mitigate the weight drift problem experienced in the conventional Least Mean Square (LMS) and Least Mean Fourth (LMF) algorithms. The main aim of this work is to derive the LLMMN adaptive algorithm and conduct transient analysis using the energy conservation relation framework. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and show improved performance obtained through the use of LLMMN over the conventional LMMN algorithm in a weight drift environment.

Original languageEnglish
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages1520-1523
Number of pages4
ISBN (Print)9781479923908
DOIs
StatePublished - 2013

Publication series

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

Keywords

  • Adaptive filters
  • leaky least mean mixed norm
  • weight drift

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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