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Exploiting Narrowband Efficiency for Broadband Convolutive Blind Source Separation

EURASIP Journal on Advances in Signal Processing20062007:016381

https://doi.org/10.1155/2007/16381

Received: 28 September 2005

Accepted: 11 June 2006

Published: 12 September 2006

Abstract

Based on a recently presented generic broadband blind source separation (BSS) algorithm for convolutive mixtures, we propose in this paper a novel algorithm combining advantages of broadband algorithms with the computational efficiency of narrowband techniques. By selective application of the Szegö theorem which relates properties of Toeplitz and circulant matrices, a new normalization is derived as a special case of the generic broadband algorithm. This results in a computationally efficient and fast converging algorithm without introducing typical narrowband problems such as the internal permutation problem or circularity effects. Moreover, a novel regularization method for the generic broadband algorithm is proposed and subsequently also derived for the proposed algorithm. Experimental results in realistic acoustic environments show improved performance of the novel algorithm compared to previous approximations.

Keywords

Information TechnologyQuantum InformationComputational EfficiencyPrevious ApproximationRegularization Method

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Authors’ Affiliations

(1)
Multimedia Communications and Signal Processing, University of Erlangen-Nuremberg, Erlangen, Germany

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Copyright

© Robert Aichner et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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