SSPA'2000 International Conference


 A Batch Subspace ICA Algorithm.

Ali MANSOUR and Noboru OHNISHI
Bio-Mimetic Control Research Center (RIKEN),
2271-130, Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463 (JAPAN)


abstract
For the blind separation of sources (BSS) problem
(or the independent component analysis (ICA)), it has been shown
in many situations, that the adaptive subspace algorithms  are very slow and
need an important computation efforts. In a previous publication, we proposed
a modified subspace algorithm for stationary signals. But that algorithm was
limited to stationary signals and its convergence was not fast enough.
 Here, we propose a batch subspace algorithm. The experimental study proves that
 this algorithm is very fast but its performance are not enough to completely achieve
 the separation of the independent component of the signals. In the other hand, this
 algorithm can be used as a pre-processing algorithm to initialized other adaptive subspace algorithms.

Keywords: blind separation of sources, ICA, subspace methods, Lagrange method, Cholesky decomposition.