The aim of this paper is to introduce a blind source separation algorithm in reverberant environment, usually characterized by long impulsive responses. In order to reduce the computational complexity of this kind of algorithms a partitioned frequency domain approach is proposed by partitioning the demixing filter in an optimal number of sub-filters. Several experimental results are shown to demonstrate the effectiveness of the proposed method.

A Partitioned Frequency Domain Algorithm for Convolutive Blind Source Separation / Scarpiniti, Michele; Picaro, A; Parisi, Raffaele; Uncini, Aurelio. - (2009), pp. 1-6. (Intervento presentato al convegno IEEE International Workshop on Machine Learning for Signal Processing tenutosi a Grenoble, France nel September 2-4, 2009) [10.1109/MLSP.2009.5306200].

A Partitioned Frequency Domain Algorithm for Convolutive Blind Source Separation

SCARPINITI, MICHELE;PARISI, Raffaele;UNCINI, Aurelio
2009

Abstract

The aim of this paper is to introduce a blind source separation algorithm in reverberant environment, usually characterized by long impulsive responses. In order to reduce the computational complexity of this kind of algorithms a partitioned frequency domain approach is proposed by partitioning the demixing filter in an optimal number of sub-filters. Several experimental results are shown to demonstrate the effectiveness of the proposed method.
2009
IEEE International Workshop on Machine Learning for Signal Processing
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A Partitioned Frequency Domain Algorithm for Convolutive Blind Source Separation / Scarpiniti, Michele; Picaro, A; Parisi, Raffaele; Uncini, Aurelio. - (2009), pp. 1-6. (Intervento presentato al convegno IEEE International Workshop on Machine Learning for Signal Processing tenutosi a Grenoble, France nel September 2-4, 2009) [10.1109/MLSP.2009.5306200].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/225612
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