Independent component analysis method and application

被引：0
|
作者：
Zhou, WD [1 ]
Jia, L [1 ]
Li, YY [1 ]
机构：
[1] Shandong Univ, Sch Informat Sci, Jinan 250100, Peoples R China
来源：
ICEMI'2001: FIFTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT AND INSTRUMENTS, VOL 1, CONFERENCE PROCEEDINGS | 2001年
关键词：
blind source separation (BSS); independent component analysis (ICA); negentropy;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the Independent component analysis (ICA) in Blind source separation (BSS) is introduced. A fast ICA algorithm is proposed. In contrast to most blind source separation algorithms, the method does not employ higher order statistics. A pre-whiten procedure is performed to de-correlating the sensor signals before extracting vector. The proposed method is verified with simulated signals and clinical electroencephalograph (EEG) signal.
引用
收藏
页码：576 / 579
页数：4
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