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Masaki HASHIZUME Teruyoshi MATSUSHIMA Takashi SHIMAMOTO Hiroyuki YOTSUYANAGI Takeomi TAMESADA Akio SAKAMOTO
A new state reduction method of incompletely specified sequential machines is proposed in this paper. The method is based on a genetic algorithm implementing a dormant mechanism. MCNC benchmark machines are simplified by using this method to evaluate the method. The experimental results show that machines of almost the same number of states as the minimum ones can be derived by this method.
Masaki HASHIZUME Takeomi TAMESADA Takashi SHIMAMOTO Akio SAKAMOTO
This paper presents two kinds of simplification methods for incompletely specified sequential machines. The strategy of the methods is that as many states in original machines are covered in the simplification processes as possible. The purpose of the methods is to derive a simplified machine having either the largest maximal compatible set or its subset. With the methods, one of the minimal machines can not be always derived, but a near-minimal machine can be obtained more quickly with less memory, since they need not derive all the compatible sets. In this paper, the effectiveness of the methods is checked by applying them to simplification problems of incompletely specified machines generated by using random numbers, and of the MCNC benchmark machines. The experimental results show that our methods can derive a simplified machine quickly, especially for machines having a great number of states or don't care rate.