Active source selection using Gap statistics for underdetermined blind source separation
conference contribution
posted on 2010-02-05, 14:58 authored by Yuhui Luo, Jonathon ChambersWe 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
© IEEEVersion
- VoR (Version of Record)
Publication date
2003Notes
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
0-7803-7946-2Language
- en
