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EURASIP Journal on Audio, Speech, and Music Processing
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Efficient Multichannel NLMS Implementation for Acoustic Echo Cancellation

EURASIP Journal on Audio, Speech, and Music Processing volume 2007, Article number: 078439 (2007) Cite this article

Abstract

An acoustic echo cancellation structure with a single loudspeaker and multiple microphones is, from a system identification perspective, generally modelled as a single-input multiple-output system. Such a system thus implies specific echo-path models (adaptive filter) for every loudspeaker to microphone path. Due to the often large dimensionality of the filters, which is required to model rooms with standard reverberation time, the adaptation process can be computationally demanding. This paper presents a selective updating normalized least mean square (NLMS)-based method which reduces complexity to nearly half in practical situations, while showing superior convergence speed performance as compared to conventional complexity reduction schemes. Moreover, the method concentrates the filter adaptation to the filter which is most misadjusted, which is a typically desired feature.

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Author information

Authors and Affiliations

  1. Konftel AB, Research and Development, Box 268, Umea, 90106, Sweden

    Fredric Lindstrom

  2. Department of Signal Processing, Blekinge Institute of Technology, Ronneby, 37225, Sweden

    Christian Schüldt & Ingvar Claesson

Authors
  1. Fredric Lindstrom
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  2. Christian Schüldt
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  3. Ingvar Claesson
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Corresponding author

Correspondence to Fredric Lindstrom.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lindstrom, F., Schüldt, C. & Claesson, I. Efficient Multichannel NLMS Implementation for Acoustic Echo Cancellation. J AUDIO SPEECH MUSIC PROC. 2007, 078439 (2007). https://doi.org/10.1155/2007/78439

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  • DOI: https://doi.org/10.1155/2007/78439

Keywords

  • Acoustics
  • Adaptive Filter
  • Complexity Reduction
  • Identification Perspective
  • Reverberation Time