Title :
Blind wideband source separation
Author :
Nájar, Montse ; Lagunas, Miguel A. ; Bonet, Ignasi
Author_Institution :
Dept. of Signal Theory & Commun., Univ. Politecnica de Catalunya, Barcelona, Spain
Abstract :
This paper deals with the general problem of separating two independent wideband sources when they are mixed by unknown filters. In order to solve this problem, a backward framework is proposed which is composed of two different stages. The first one consists of two linear predictors devoted to improve the source separation, whitening the input signals. Their coefficients are calculated applying the LMS algorithm, minimizing the mean squared errors between the predicted signals and the output of the separation network. The second stage is formed by decoupling filters that have to be blindly estimated imposing an independence criterion to the outputs
Keywords :
adaptive estimation; adaptive signal processing; filtering theory; least mean squares methods; prediction theory; LMS algorithm; adaptive signal estimation; backward framework; blind wideband source separation; coefficients; decoupling filters; filters; input signals whitening; linear predictors; mean squared errors; predicted signals; separation network; Apertures; Array signal processing; Filtering theory; Filters; Least squares approximation; Sensor arrays; Source separation; Transfer functions; White noise; Wideband;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389875
