Title :
A partitioned frequency domain algorithm for convolutive blind source separation
Author :
Scarpiniti, Michele ; Picaro, Andrea ; Parisi, Raffaele ; Uncini, Aurelio
Author_Institution :
Infocom Dept., Sapienza Univ. of Rome, Rome, Italy
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.
Keywords :
blind source separation; computational complexity; convolution; filtering theory; frequency-domain analysis; transient response; computational complexity; convolutive blind source separation algorithm; demixing filter; impulsive response; partitioned frequency domain algorithm; Blind source separation; Computational complexity; Convolution; Finite impulse response filter; Frequency domain analysis; Frequency estimation; Partitioning algorithms; Reverberation; Sensor arrays; Source separation;
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
Electronic_ISBN :
978-1-4244-4948-4
DOI :
10.1109/MLSP.2009.5306200
