Title :
Blind separation of non stationary sources using joint block diagonalization
Author :
Bousbia-Salah, Hicham ; Belouchrani, Adel ; Abed-Meraim, Karim
Author_Institution :
Electr. Eng. Dept., Ecole Nationale Polytechnique, Algiers, Algeria
fDate :
6/23/1905 12:00:00 AM
Abstract :
Recovering independent source signals from their convolutive mixtures without any a priori knowledge on their structure represents a great challenge in signal processing. We present an efficient solution that is based on the joint block-diagonalization of positive spatio-temporal covariance matrices. In the case of instantaneous mixtures, robust solutions have been proposed previously. Taking advantage of possible non-stationarity of the sources, this new technique uses only second order statistics. The new approach has been successfully applied to the separation of speech signals
Keywords :
covariance matrices; deconvolution; speech processing; statistical analysis; blind source separation; convolutive mixtures; deconvolution; joint block diagonalization; non-stationary sources; positive covariance matrices; second order statistics; signal processing; spatio-temporal covariance matrices; speech signals; Covariance matrix; Data models; Deconvolution; Equalizers; Filters; Image processing; MIMO; Robustness; Signal processing; Speech;
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
DOI :
10.1109/SSP.2001.955319