Soft computing for feature analysis

被引：46

作者：

Pal, NR ^{[1
]}

机构：

[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700035, W Bengal, India

来源：

FUZZY SETS AND SYSTEMS | 1999年 / 103卷 / 02期

关键词：

soft computing; feature selection; connectionist models; feature attenuators; dimensionality reduction; feature ranking;

D O I：

10.1016/S0165-0114(98)00222-X

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

With an introduction to soft computing we discuss how the three main ingredients, fuzzy logic, neural networks and genetic algorithms can play significant roles in the design of successful pattern recognition systems. Then we concentrate only on one aspect of pattern recognition, feature analysis, and discuss various methods using fuzzy logic, neural networks and genetic algorithms for feature ranking, selection and extraction including structure preserving dimensionality reduction. Finally, the methods are illustrated with both real and synthetic data. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：201 / 221

页数：21

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