Abstract

A finite automaton consists of a finite set of states and a set of transitions from state to state that occur on input symbols. When the states of a finite automaton are characterized by fuzzy sets, the outputs and transitions are facilitated by appropriate relation, then this finite automaton is called a fuzzy automaton. Two states of fuzzy automaton have similarity relation as they have the similar degree from itself to the final state for any arbitrary input symbol. Based on the clustering technique, we present an algorithm to minimize the states of fuzzy automaton.

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