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Principle Component Analysis

Principle Component Analysis

David Zhang, Xiao-Yuan Jing, Jian Yang
Copyright: © 2006 |Pages: 20
ISBN13: 9781591408307|ISBN10: 159140830X|ISBN13 Softcover: 9781591408314|EISBN13: 9781591408321
DOI: 10.4018/978-1-59140-830-7.ch002
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MLA

David Zhang, et al. "Principle Component Analysis." Biometric Image Discrimination Technologies: Computational Intelligence and its Applications Series, IGI Global, 2006, pp.21-40. https://doi.org/10.4018/978-1-59140-830-7.ch002

APA

D. Zhang, X. Jing, & J. Yang (2006). Principle Component Analysis. IGI Global. https://doi.org/10.4018/978-1-59140-830-7.ch002

Chicago

David Zhang, Xiao-Yuan Jing, and Jian Yang. "Principle Component Analysis." In Biometric Image Discrimination Technologies: Computational Intelligence and its Applications Series. Hershey, PA: IGI Global, 2006. https://doi.org/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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