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. © 2011 The authors and IOS Press. All rights reserved.
A Geometrically Constrained ICA Algorithm for Blind Separation in Convolutive Environments / Scarpiniti, Michele; F., Di Palma; Parisi, Raffaele; Uncini, Aurelio. - 226(2011), pp. 79-88. - FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS. [10.3233/978-1-60750-692-8-79].
A Geometrically Constrained ICA Algorithm for Blind Separation in Convolutive Environments
SCARPINITI, MICHELE;PARISI, Raffaele;UNCINI, Aurelio
2011
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. © 2011 The authors and IOS Press. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.