Independent Subspace Analysis Using Three Scatter Matrices

被引：0
|
作者：
Nordhausen, Klaus [1 ]
Oja, Hannu [1 ]
机构：
[1] Univ Tampere, Sch Hlth Sci, FIN-33014 Tampere, Finland
来源：
AUSTRIAN JOURNAL OF STATISTICS | 2011年 / 40卷 / 1-2期
基金：
芬兰科学院;
关键词：
Independent Component Analysis; Source Separation;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In independent subspace analysis (ISA) one assumes that the components of the observed random vector are linear combinations of the components of a latent random vector with independent subvectors. The problem is then to find an estimate of a transformation matrix to recover the independent subvectors. Regular independent component analysis (ICA) is a special case. In this paper we show how three scatter matrices with the so called block independence property can be used in independent subspace analysis. The procedure is illustrated with a small example.
引用
收藏
页码：93 / 101
页数：9
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