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.
2011
Neural Nets WIRN10
9781607506911
convolutive environment; fastica; frequency domain algorithms; blind source separation; geometrical constraints
02 Pubblicazione su volume::02a Capitolo o Articolo
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].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/167477
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