Gradient algorithms for principal component analysis

被引：9
|
作者：
Mahony, RE [1 ]
Helmke, U [1 ]
Moore, JB [1 ]
机构：
[1] UNIV REGENSBURG,DEPT MATH,W-8400 REGENSBURG,GERMANY
来源：
JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY SERIES B-APPLIED MATHEMATICS | 1996年 / 37卷
关键词：
D O I：
10.1017/S033427000001078X
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The problem of principal component analysis of a symmetric matrix (finding a p-dimensional eigenspace associated with the largest p eigenvalues) can be viewed as a smooth optimization problem on a homogeneous space. A solution in terms of the limiting value of a continuous-time dynamical system is presented, A discretization of the dynamical system is proposed that exploits the geometry of the homogeneous space. The relationship between the proposed algorithm and classical methods are investigated.
引用
收藏
页码：430 / 450
页数：21
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