Online Subband Blind Source Separation for Convolutive Mixtures Using a Uniform Filter Bank with Critical Sampling

Authors:
Paulo B. Batalheiro;Mariane R. Petraglia;Diego B. Haddad
Affiliations:
CTC/FEN/DETEL, State University of Rio de Janeiro, Rio de Janeiro, Brazil 20559-900;PEE/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil 21945-970;CEFET-RJ, Federal Center for Technological Education, Nova Iguaçu, Brazil
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 5
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Abstract

Adaptive subband structures have been proposed with the objective of increasing the convergence speed and/or reducing the computational complexity of adaptation algorithms for applications which require a large number of adaptive coefficients. In this paper we propose an online blind source separation method for convolutive mixtures which employs a real-coefficient uniform subband structure with critical sampling and extra filters that cancel aliasing between adjacent channels. Since the separation filters in the subbands work at reduced sampling rates, the proposed method presents smaller computational complexity and larger steady-state signal to noise interference ratio when compared to the corresponding fullband algorithm.