A modified underdetermined blind source separation algorithm using competitive learning

S Loncaric (Editor), A Neri, H Babic (Editor)

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

The problem of underdetermined blind source separation is addressed. An advanced classification method based upon competitive learning is proposed for automatically determining the number of active sources over the observation. Its introduction in underdetermined blind source separation successfully overcomes the drawback of an existing method, in which the goal of separating more sources than the number of available mixtures is achieved by exploiting the sparsity of the nonstationary sources in the time-frequency domain. Simulation studies are presented to support the proposed approach. (7 References).

Conference

ConferenceISPA 2004. Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis (IEEE Cat. No.03EX651). Univ. of Zagreb. Part Vol.2, 2003, pp.966-9 Vol.2. Zagreb, Croatia.
Period1/01/2003 → …

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