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Active source selection using Gap statistics for underdetermined blind source separation

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conference contribution
posted on 05.02.2010, 14:58 by Yuhui Luo, Jonathon Chambers
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.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

LUO, Y. and CHAMBERS, J.A., 2003. Active source selection using Gap statistics for underdetermined blind source separation. IN: Proceedings of 2003 7th International Symposium on Signal Processing and Its Applications (ISSPA 2003), Paris, France, 1-4 July, Vol. 1, pp. 137-140.

Publisher

© IEEE

Version

VoR (Version of Record)

Publication date

2003

Notes

This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

0-7803-7946-2

Language

en

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Keywords

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