Principle Component Analysis

View Sample PDF

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

Keywords: Biometrics / Biotechnology and Bioinformatics / Engineering Science Reference / Medicine & Healthcare

Purchase

View Principle Component Analysis on the publisher's website for pricing and purchasing information.

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.

The IRMA Community

Research IRM

Principle Component Analysis

Purchase

Abstract

Related Content

IRMA Sponsors