CONSTRUCTION OF FEATURES AND DECISION RULES IN FUZZY PATTERN RECOGNITION TASKS

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 membe...

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Bibliographic Details
Published inInternational journal of general systems Vol. 30; no. 1; pp. 23 - 43
Main Authors BORISOV, ARKADY, OZOLS, JURIS, GREKOV, ROMAN
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.01.2001
Subjects
compositions of fuzzy relations
feature extraction
fuzzy objects
fuzzy relations
Pattern recognition
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Summary: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.
ISSN:0308-1079
1563-5104
DOI:10.1080/03081070108960696