Representation and identification method of finite state automata by recurrent high-order neural networks

Authors:
Yasuaki Kuroe
Affiliations:
Center for Information Science, Kyoto Institute of Technology, Kyoto, Japan
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

This paper presents a new architecture of neural networks for representing deterministic finite state automata. The proposed model is a class of high-order recurrent neural networks. It is capable of representing FSA with the network size being smaller than the existing models proposed so far. We also propose an identification method of FSA from a given set of input and output data by training the proposed model of neural networks.