Introduction to Automata Theory, Languages and Computability
Introduction to Automata Theory, Languages and Computability
Characterizing the super-Turing computing power and efficiency of classical fuzzy Turing machines
Theoretical Computer Science - Super-recursive algorithms and hypercomputation
A First Course in Fuzzy Logic, Third Edition
A First Course in Fuzzy Logic, Third Edition
On the computing power of fuzzy Turing machines
Fuzzy Sets and Systems
Intuitionistic fuzzy recognizers and intuitionistic fuzzy finite automata
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Lattice-valued fuzzy Turing machines: Computing power, universality and efficiency
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Fuzzy and probabilistic programs
Information Sciences: an International Journal
Fuzzy Turing Machines: Variants and Universality
IEEE Transactions on Fuzzy Systems
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First we define a new class of fuzzy Turing machines that we call Generalized Fuzzy Turing Machines. Our machines are equipped with rejecting states as well as accepting states. While we use a t-norm for computing degrees of accepting or rejecting paths, we use its dual t-conorm for computing the accepting or rejecting degrees of inputs. We naturally define when a generalized fuzzy Turing machine accepts or decides a fuzzy language. We prove that a fuzzy language L is decidable if and only if L and its complement are acceptable. Moreover, to each r.e. or co-r.e language L, we naturally correspond a fuzzy language which is acceptable by a generalized fuzzy Turing machine. A converse to this result is also proved. We also consider Atanasov's intuitionistic fuzzy languages and introduce a version of fuzzy Turing machine for studying their computability theoretic properties.