DSPA'98

Subspace Adaptive Algorithm  For Blind Separation Of Convolutive Mixtures 
By Conjugate Gradient Method.

A. Mansour, A. Kardec Barros and N. Ohnishi
Bio-Mimetic Control Research Center (RIKEN),
2271-130, Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463 (JAPAN)
abstract

In this paper, a new subspace adaptive algorithm,
for blind separation of convolutive mixture, is proposed.
This algorithm can be decomposed into two steps: At first,
the convolutive mixture will be reduced to an instantaneous mixture
(memoryless mixture), using a second-order statistics criterion based
on subspace approach. The second step consists on the separation of the
residual instantaneous mixture.

The minimization of the criterion is achieved using a conjugate gradient method.
The experimental results show that the convergence of our algorithm is improved
thanks to the use of  the conjugate gradient method.
 Finally, experimental results are shown.