Blind separation of sources: Methods, assumptions and applications

被引：0
|
作者：
Mansour, A [1 ]
Barros, AK
Ohnishi, N
机构：
[1] RIKEN, Biomimet Control Res Ctr, Nagoya, Aichi 463003, Japan
[2] Nagoya Univ, Dept Informat Engn, Nagoya, Aichi 46401, Japan
来源：
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2000年 / E83A卷 / 08期
关键词：
independent component analysis (ICA); contrast function; Kullback-Leibner divergence; prediction error; subspace; decorrelation; high order statistics; whitening; mutual-information; likelihood maximization; conjoint diagonalization;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The blind separation of sources is a recent and important problem in signal processing. Since 1984 [1], it has been studied by many authors whilst many algorithms have been proposed. In this paper, the description of the problem, its assumptions, its currently applications and some algorithms and ideas are discussed.
引用
收藏
页码：1498 / 1512
页数：15
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