Independent component analysis: source assessment and separation, a Bayesian approach

被引：36
|
作者：
Roberts, SJ [1 ]
机构：
[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, Neural Syst Res Grp, London SW7 2BT, England
来源：
IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING | 1998年 / 145卷 / 03期
关键词：
independent component analysis; source separation; Bayesian analysis;
D O I：
10.1049/ip-vis:19981928
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：
The author presents a method of independent component analysis which assesses the most probable number of source sequences from a larger number of observed sequences and estimates the unknown source sequences and mixing matrix. The estimation of the number of true sources is regarded as a model-order estimation problem and is tackled under a Bayesian paradigm. The method is shown to give good results on both synthetic and real data.
引用
收藏
页码：149 / 154
页数：6
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