We show that the size reduction problem for fuzzy automata is related to the problem of solving a particular system of fuzzy relation equations. This system consists of infinitely many equations, and finding its general solution is a very difficult task, so we first consider one of its special cases, a finite system whose solutions, called right invariant fuzzy equivalences, are common generali...

In this paper a combination of neuro-fuzzy classifiers for improved classification performance and reliability is considered. A general fuzzy min-max (GFMM) classifier with agglomerative learning algorithm is used as a main building block. An alternative approach to combining individual classifier decisions involving the combination at the classifier model level is proposed. The resulting class...

Abstract. In this paper, lexicographic products of two fuzzy graphs namely, lexicographic min-product and lexicographic max-product which are analogous to the concept lexicographic product in crisp graph theory are defined. It is illustrated that the operations lexicographic products are not commutative. The connected, effective and complete properties of the operations lexicographic products a...

 ‎Let $tilde{F}=(Q,S,tilde{R},Z,omega,tilde{delta},‎ F_1,F_2)$‎ ‎be a general fuzzy automaton and the set of its states be a group.‎ ‎The aim of this paper is the study of applications of a group in a‎ ‎general fuzzy automaton‎. ‎For this purpose‎, ‎we define the concepts‎ ‎of fuzzy normal kernel of a general fuzzy automaton‎, ‎fuzzy kernel‎ ‎of a general fuzzy automaton‎, ‎adjustable‎, ‎multip...

The paper studies the relationship among fuzzy context free languages and fuzzy push down automata. The degree of membership of the words to the fuzzy language generated by a context free grammar, calculated in a monoid, introduces an additional burden for the accepting push down weighted automaton. Even in the case of languages accepted by fuzzy deterministic push down automata, the relationsh...

In computer vision, image segmentation is an important problem and plays vital role in medical imaging. Analysis and diagnosis of tumor in MRI brain image involves segmentation as very essential steep. It separates the region of interest objects from the background and the other objects. Several approaches are used for MRI brain tumor segmentation. Fuzzy C Means (FCM) is most widely used fuzzy ...

There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson’s fuzzy min-max neural ne...

The extension of standard concepts of set theory (like union, intersection, etc.) to the theory of fuzzy sets is not obvious. Several policies for answering questions of this type have been discussed, but it appears that the operations of max and min play a central role in the arithmetic of fuzzy sets. Letting Pi denote our willingness to accept x as a member in the fuzzy set A, Zadeh defines i...