A practical sequential method for principal component analysis

被引:10
作者
Wong, ASY
Wong, KW
Leung, CS
机构
[1] City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
[2] Nanyang Technol Univ, Sch Appl Sci, Singapore 2263, Singapore
关键词
principal component analysis; sequential extraction;
D O I
10.1023/A:1009646500088
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When increasing numbers of principal components are extracted by using the sequential method proposed in [1] by Banour and Azimi-Sadjadi, the accumulated extraction error will become dominant and affect the extractions of the remaining principal components. To improve this, we suggest that the initial weight vector for the extraction of the next component should be orthogonal to the eigensubspace spanned by the already extracted weight vectors. Simulation results show that both the convergence and the accuracy of the extraction are improved. Our improved method is also capable of extracting full eigenspace accurately.
引用
收藏
页码:107 / 112
页数:6
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