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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
