A New Mixing Matrix Identification Algorithm for Underdetermined Blind Source Separation

被引：3
|
作者：
Zhang, Zhong [1 ]
Zhang, Xudong [1 ]
机构：
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
来源：
ICSP: 2008 9TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-5, PROCEEDINGS | 2008年
关键词：
underdetermined blind source separation; sparse component analyses; independent component analysis;
D O I：
10.1109/ICOSP.2008.4697122
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we focus on the mixing matrix identification problem for underdetermined blind source separation. Based on the two-stage approach in sparse component analysis[1], we proposal a new algorithm that integrate with other blind signal processing methods like independent component analysis and model order selection. Compared with the DUET, the TIFROM and standard clustering methods, this algorithm can work adaptively in noisy environment and the required sparseness of sources can be considerably relaxed. Simulation results are presented.
引用
收藏
页码：268 / 271
页数：4
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