A low complexity fast converging partial update adaptive algorithm employing variable step-size for acoustic echo cancellation

Andy W.H. Khong, Woon Seng Gan, Patrick A. Naylor, Mike Brookes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Partial update adaptive algorithms have been proposed as a means of reducing complexity for adaptive filtering. The MMax tap-selection is one of the most popular tap-selection algorithms. It is well known that the performance of such partial update algorithm reduces with reducing number of filter coefficients selected for adaptation. We propose a low complexity and fast converging adaptive algorithm that exploits the MMax tap-selection. We achieve fast convergence with low complexity by deriving a variable step-size for the MMax normalized least-mean-square (MMax-NLMS) algorithm using its mean square deviation. Simulation results verify that the proposed algorithm achieves higher rate of convergence with lower computational complexity compared to the NLMS algorithm.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages237-240
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

ASJC Scopus Subject Areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Acoustic echo cancellation
  • Adaptive algorithms
  • Partial update adaptive filtering
  • Variable step-size

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