A Method for Filter Equalization in Convolutive Blind Source Separation

Radoslaw Mazur, Alfred Mertins


The separation of convolutive mixed signals can be carried out in the time-frequency domain, where the task is reduced to multiple instantaneous problems. This direct approach leads to the permutation and scaling problems, but it is possible to introduce an objective function in the time-frequency domain and minimize it with respect to the time domain coefficients. While this approach allows for the elimination of the permutation problem, the unmixing filters can be quite distorted due the unsolved scaling problem. In this paper we propose a method for equalization of these filters by using the scaling ambiguity. The resulting filters have a characteristic of a Dirac pulse and introduce less distortion to the separated signals. The results are shown on a real-world example.
TitelLatent Variable Analysis and Signal Separation
Redakteure/-innenVincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent
Band6365 LNCS
ErscheinungsortBerlin, Heidelberg
Herausgeber (Verlag)Springer Berlin Heidelberg
ISBN (Print)978-3-642-15994-7
ISBN (elektronisch)978-3-642-15995-4
PublikationsstatusVeröffentlicht - 01.09.2010


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