Active source selection using gap statistics for underdetermined blind source separation

被引：2
|
作者：
Luo, Y [1 ]
Chambers, J [1 ]
机构：
[1] Kings Coll London, Sch Phys Sci & Engn, Ctr Digital Signal Proc Res, London WC2R 2LS, England
来源：
SEVENTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOL 1, PROCEEDINGS | 2003年
关键词：
D O I：
10.1109/ISSPA.2003.1224659
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：137 / 140
页数：4
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