Blind extraction of singularly mixed source signals

Authors:
Zhigang Zeng;Chaojin Fu
Affiliations:
School of Automation, Wuhan University of Technology, Wuhan, Hubei, China;Department of Mathematics, Hubei Normal University, Huangshi, Hubei, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Abstract

In this paper, a neural network model and its associate learning rule are developed for sequential blind extraction in the case that the number of observable mixed signals is less than the one of sources. This approach is also suitable for the case in which the mixed matrix is nonsingular. Using this approach, all separable sources can be extracted one by one. The solvability analysis of the problem is also presented, and the new solvable condition is weaker than existing solvable conditions in some literatures.