Construction of features and decision rules in fuzzy pattern recognition tasks

被引：0

作者：

Borisov, A ^{[1
]}

Ozols, J ^{[1
]}

Grekov, R ^{[1
]}

机构：

[1] Riga Tech Univ, Inst Informat Technol, Decis Support Syst Grp, LV-1658 Riga, Latvia

来源：

INTERNATIONAL JOURNAL OF GENERAL SYSTEMS | 2001年 / 30卷 / 01期

关键词：

pattern recognition; fuzzy objects; fuzzy relations; compositions of fuzzy relations; feature extraction;

D O I：

10.1080/03081070108960696

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper examines the search of effective features sets that maximize an increase in the system's recognition ability. The comparison of binary relations composition is used as a basis for evaluation methods. Binary relations compositions are obtained as a result of shadow operations on membership functions values. Special attention is paid to the study of the structure of composition graphs. The view of the graph enables one to assess the recognition ability of a parameter or a feature. The proposed methods enable the evaluation of a single parameter or a group of parameters (features). This allows the selection of a more precise efficient feature set and, in the long run, improves the quality of recognition.

引用

页码：23 / 43

页数：21