A novel method for Fisher discriminant analysis

被引：74

作者：

Xu, Y ^{[1
]}

Yang, JY ^{[1
]}

Jin, Z ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Dept Comp Sci, Nanjing 210094, Peoples R China

来源：

PATTERN RECOGNITION | 2004年 / 37卷 / 02期

关键词：

Fisher discriminant analysis; FSLDA (Foley Sammon linear discriminant analysis); ULDA (uncorrelated linear discriminant analysis);

D O I：

10.1016/S0031-3203(03)00232-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A novel model for Fisher discriminant analysis is developed in this paper. In the new model, maximal Fisher criterion values of discriminant vectors and minimal statistical correlation between feature components extracted by discriminant vectors are simultaneously required. Then the model is transformed into an extreme value problem, in the form of an evaluation function. Based on the evaluation function, optimal discriminant vectors are worked out. Experiments show that the method presented in this paper is comparative to the winner between FSLDA and ULDA. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：381 / 384

页数：4

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