Some concepts in Fuzzy Generalized Automata (FGA) are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts: the first is called E-r...Some concepts in Fuzzy Generalized Automata (FGA) are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts: the first is called E-reduction which contracts equivalent states, and the second is called RE-reduction which removes retrievable states. Finally an example is given to illuminate the algorithm of minimization.展开更多
This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given re...This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given respectively. The application example given at last shows the effectiveness of the proposed evolution strategy for automata induction.展开更多
At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introdu...At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.展开更多
基金Supported by Supported by National Natural Science Foundation of China (No.60074014)
文摘Some concepts in Fuzzy Generalized Automata (FGA) are established. Then an important new algorithm which would calculate the minimal FGA is given. The new algorithm is composed of two parts: the first is called E-reduction which contracts equivalent states, and the second is called RE-reduction which removes retrievable states. Finally an example is given to illuminate the algorithm of minimization.
文摘This paper presents an evolution strategy to induce fuzzy finite-state automata from examples of fuzzy languages. The coding, fitness function of a generated automaton and corresponding mutation operators are given respectively. The application example given at last shows the effectiveness of the proposed evolution strategy for automata induction.
基金Youth Science and Technology Foundation of Sichuan (No. L080011YF021104)
文摘At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.