Robust blind source separation utilizing second and fourth order statistics

被引：0
|
作者：
Georgiev, P [1 ]
Cichocki, A [1 ]
机构：
[1] RIKEN, Brain Sci Inst, Wako, Saitama 3510198, Japan
来源：
ARTIFICIAL NEURAL NETWORKS - ICANN 2002 | 2002年 / 2415卷
关键词：
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：
We introduce identifiability conditions for the blind source separation (BSS) problem, combining the second and fourth order statistics. We prove that under these conditions, well known methods (like eigen-value decomposition and joint diagonalization) can be applied with probability one, i.e. the set of parameters for which such a method doesn't solve the BSS problem, has a measure zero.
引用
收藏
页码：1162 / 1167
页数：6
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