Solving the Permutation Problem in Convolutive Blind Source Separation

Radoslaw Mazur, Alfred Mertins


This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.
Original languageEnglish
Title of host publicationIndependent Component Analysis and Signal Separation
EditorsMike E. Davies, Christopher J. James, Samer A. Abdallah, Mark D. Plumbley
Number of pages8
Volume4666 LNCS
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Publication date01.09.2007
ISBN (Print)978-3-540-74493-1
ISBN (Electronic)978-3-540-74494-8
Publication statusPublished - 01.09.2007
Event7th International Conference on Independent Component Analysis (ICA) and Source Separation - London, United Kingdom
Duration: 09.09.200712.09.2007
Conference number: 70941


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