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Energy constrained frequency-domain normalized LMS algorithm for blind channel identification

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Abstract

This paper deals with the blind adaptive identification of single-input multi-output (SIMO) finite impulse response acoustic channels from noise-corrupted observations. The normalized multichannel frequency-domain least-mean-squares (NMCFLMS) algorithm [1] is known to be a very effective and efficient technique for identification of such channels when noise effects can be ignored. It, however, misconverges in presence of noise [2]. In this paper, we present an analysis of noise effects on the NMCFLMS algorithm and propose a novel technique for ameliorating such misconvergence characteristics of the NMCFLMS algorithm for blind channel identification (BCI) with noise by attaching a spectral constraint in the adaptation rule. Experimental results demonstrate that the robustness of the NMCFLMS algorithm for BCI can be significantly improved using such a constraint.

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Abbreviations

α:

arbitrary constant

β:

Lagrangian multiplier

γ:

smoothing parameter

γ e :

positive real constant

η:

positive real constant

λ:

eigenvalue

ρ:

step size

τ:

separation between microphones

J :

cost function

R :

autocorrelation matrix

M :

number of channels

L :

length of channel impulse response

s :

clean speech

y :

reverberant speech

x :

reverberant speech corrupted by noise

v :

observation noise

h :

channel impulse response

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh

    M. Ariful Haque, M. Shafi Al Bashar & Md. Kamrul Hasan

  2. Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK

    Patrick A. Naylor

  3. Department of Information and Communication Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku,Tokyo, Japan

    Keikichi Hirose

Authors
  1. M. Ariful Haque
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  2. M. Shafi Al Bashar
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  3. Patrick A. Naylor
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  4. Keikichi Hirose
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  5. Md. Kamrul Hasan
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Corresponding author

Correspondence to Md. Kamrul Hasan.

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Haque, M.A., Bashar, M.S.A., Naylor, P.A. et al. Energy constrained frequency-domain normalized LMS algorithm for blind channel identification. SIViP 1, 203–213 (2007). https://doi.org/10.1007/s11760-007-0011-x

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  • DOI: https://doi.org/10.1007/s11760-007-0011-x

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