Active source selection using gap statistics for underdetermined blind source separation

Y Luo; J Chambers

doi:10.1109/ISSPA.2003.1224659

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Active source selection using gap statistics for underdetermined blind source separation

Y Luo and J Chambers

Proceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003, Vol.1, pp.137-140

01/01/2003

DOI: https://doi.org/10.1109/ISSPA.2003.1224659

Abstract

We address the problem of automatically determining the number of active sources in underdetermined blind source separation (BSS). A time-frequency approach to underdetermined BSS is exploited to discriminate the time-frequency structure of the measured mixtures. To determine the number of active sources over an observation interval, an advanced clustering technique based on gap statistics is proposed. Simulation studies are presented to support the proposed approach. © 2003 IEEE.

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Title: Active source selection using gap statistics for underdetermined blind source separation
Creators: Y Luo
J Chambers
Publication Details: Proceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003, Vol.1, pp.137-140
Date published: 01/01/2003
Date submitted: 17/05/2017
Identifiers: 99514374302346
Academic Unit: University of Surrey
Resource Type: Conference presentation

Active source selection using gap statistics for underdetermined blind source separation

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