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Principle Component Analysis

Principle Component Analysis
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Author(s): David Zhang (Hong Kong Polytechnic University, Hong Kong), Xiao-Yuan Jing (ShenZhen Graduate School of Harbin Institute of Technology, China)and Jian Yang (Hong Kong Polytechnic University, Hong Kong)
Copyright: 2006
Pages: 20
Source title: Biometric Image Discrimination Technologies: Computational Intelligence and its Applications Series
Source Author(s)/Editor(s): David Zhang (Hong Kong Polytechnic University, Hong Kong ), Xiao-Yuan Jing (ShenZhen Graduate School of Harbin Institute of Technology, China)and Jian Yang (Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-59140-830-7.ch002

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Abstract

In this chapter, we first describe some basic concepts of PCA, a useful statistical technique that can be used in many fields, such as face patterns and other biometrics. Then, we introduce PCA definitions and related technologies. Following, we discuss non-linear PCA technologies. Finally, some useful conclusions are summarized.

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