Analysis and synthesis of fuzzy systems by the use of probabilistic sets

Authors:
K. Hirota;W. Pedrycz
Affiliations:
-;-
Venue:
Fuzzy Sets and Systems
Year:
1983

Citing 1
Cited 1

Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms

Applications of fuzzy relational equations for methods of reasoning in presence of fuzzy data

Fuzzy Sets and Systems

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Abstract

The paper deals with an application of probabilistic sets in system theory, especially in identification problems in systems described by means of max-min fuzzy relational equations. The identification procedures discussed are based on some ideas of iterative clustering techniques (ISODATA and FUZZY C-MEANS) which lead to a concrete method of determination of probabilistic sets. A vagueness function associated with the fuzzy relation of the system forms a validity indicator of the identification algorithm. Numerical examples containing fuzzy and nonfuzzy data form an illustration of the methods provided.