A formal power series approach to the construction of minimal fuzzy automata

Abstract A new approach to the problem of construction of minimal fuzzy automata using formal power-series representation is presented. The proceduie involves automated inference of regular fuzzy grammar from a set of sample strings. The technique yields a minimal fuzzy automaton that recognizes the positive samples of the language. The desired automata are inferred from a finite submatrix of the fuzzy Hankel matrix of the coefficients of formal power series representing the set of strings of the given language. An application in pattern recognition is shown for the inference of fuzzy grammar.

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