Robust Blind Source Separation Utilizing Second and Fourth Order Statistics

Authors:
Pando Georgiev;Andrzej Cichocki
Affiliations:
-;-
Venue:
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Year:
2002

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Abstract

We introduce identifiability conditions for the blind source separation (BSS) problem, combining the second and fourth order statistics. We prove that under these conditions, well known methods (like eigen-value decomposition and joint diagonalization) can be applied with probability one, i.e. the set of parameters for which such a method doesn't solve the BSS problem, has a measure zero.