Proportionate frequency domain adaptive algorithms for blind channel identification

Rehan Ahmad*, Andy W.H. Khong, Patrick A. Naylor

*Corresponding author for this work

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

21 Citations (Scopus)

Abstract

We present fast-converging adaptive blind channel identification algorithms for acoustic room impulse responses. These new algorithms exploit the fast-convergence of the improved proportionate normalized least-mean-square (IPNLMS) algorithm and address the problem of delay inherent in frequency domain algorithms by employing the multi-delay filter (MDF) structure. Simulation results for both speech and white Gaussian noise show that the proposed algorithms outperform current frequency domain blind channel estimation algorithms.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesV29-V32
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
ISSN (Print)1520-6149

Conference

Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Country/TerritoryFrance
CityToulouse
Period5/14/065/19/06

ASJC Scopus Subject Areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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