Title :
Associations of fuzzy sets
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
Abstract :
The concept of hierarchical models of associations of fuzzy sets (linguistic labels) is discussed. Three basic levels of hierarchy (relational, set-theoretic, and scalar) facilitate the handling of a variety of relationships between fuzzy sets. Learning mechanisms capable of discovering parameters of the models introduced are studied. The inverse problem in models of associations is formulated along with a construction of diverse forms of matching achieved there. An illustrative numerical example in pattern classification is also presented
Keywords :
fuzzy set theory; inverse problems; learning (artificial intelligence); pattern recognition; fuzzy relational equations; fuzzy sets associations; hierarchical models; inverse problem; learning mechanisms; linguistic labels; pattern classification; Artificial intelligence; Context modeling; Decision making; Fuzzy sets; Inverse problems; Learning automata; Learning systems; Pattern classification; Pattern recognition; Prototypes;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
