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Proceedings Paper

Temporal minimum entropy and minimum mutual information criteria of nonstationary signals for blind source separation
Author(s): Hsiao-Chun Wu
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Paper Abstract

The information-theoretic network for independent component analysis has been studied for unsupervised learning in the signal processing area. We derive a learning rule from the mutual information or the sum of the marginal entropy based on the local-Gaussian assumption for blind source separation of the convolutive mixture. The algorithm has been tested for several real-world recordings and showed the promising results.

Paper Details

Date Published: 8 July 1998
PDF: 9 pages
Proc. SPIE 3389, Hybrid Image and Signal Processing VI, (8 July 1998); doi: 10.1117/12.316550
Show Author Affiliations
Hsiao-Chun Wu, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 3389:
Hybrid Image and Signal Processing VI
David P. Casasent; Andrew G. Tescher, Editor(s)

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