Representation of Fuzzy Finite State
نویسندگان
چکیده
Based on previous work on encoding deterministic nite-state automata (DFAs) in discrete-time, second-order recurrent neural networks with sigmoidal discriminant functions, we propose an algorithm that constructs an augmented recurrent neural network that encodes fuzzy nite-state automata (FFAs). Given an arbitrary FFA, we apply an algorithm which transforms the FFA into an equivalent deterministic acceptor which computes the fuzzy string membership function. The neural network can be constructed such that it recognizes strings of fuzzy regular languages with arbitrary accuracy.
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