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Proceedings Paper

Simultaneous diagonalization algorithm for blind source separation based on subband filtered features
Author(s): Hsiao-Chun Wu; Jose C. Principe
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Paper Abstract

Blind source separation (BSS) has received increased attention in the signal processing literature. the goal of blind source separation is signal recovery from an unknown channel through the maximization (or minimization) of some independence criterion. In our previous work, we derived a generalized criterion (simultaneous diagonalization of correlation matrices -- SDOC) for blind source separation and explored the time-frequency structure of nonstationary signals like speech. In this paper we analyze first the identifiability of sources and apply subband filters for feature extraction to improve the BSS performance of the SDOC algorithm in the realistic but difficult situation when the background noise is not negligible.

Paper Details

Date Published: 17 July 1998
PDF: 9 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327121
Show Author Affiliations
Hsiao-Chun Wu, Univ. of Florida (United States)
Jose C. Principe, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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