A Geometrically Constrained ICA Algorithm for Blind Separation in Convolutive Environments

Authors:
Michele Scarpiniti;Francesco Di Palma;Raffaele Parisi;Aurelio Uncini
Affiliations:
Infocom Department, “Sapienza” University of Rome;Infocom Department, “Sapienza” University of Rome;Infocom Department, “Sapienza” University of Rome;Infocom Department, “Sapienza” University of Rome
Venue:
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
Year:
2011

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Abstract

In this paper a blind source separation algorithm in convolutive environment is presented. In order to avoid the classical permutation ambiguity in the frequency domain solution, a geometrical constraint is considered. Moreover a beam-former algorithm is integrated with the proposed solution: in this way the directivity pattern of the proposed architecture can take into account the residual permutation at low frequencies and the scaling inconsistency. Several experimental results are shown to demonstrate the effectiveness of the proposed method.