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Neural simulation of Petri nets.

Chen, S.W.; Fang, C.Y.; Chang, K.E.

In: Parallel Computing, Vol. 25, No. 2, pages 183-207. 1999.

Abstract: Petri nets and neural networks share a number of analogies. Investigations of their relationships can be sorted into two categories: (a) the modeling of neural activities with Petri nets, and (b) the neural simulation of Petri nets. The work presented in this paper belongs to the second category. Unlike divide-and-conquer approaches, the proposed method settles the extraneous skeleton of simulators. Inherent distinctions of Petri nets are characterized by the individual constituents of simulators. The constructed simulators thus reveal a consistently uniform structure on a macroscopic level. Compared with those generated by the divide-and-conquer approaches, ours look much portable and are empirically economic. Furthermore, in a fully parallel machine with enough nodes the overall time complexity of the neural simulator will be constant.

Keywords: Petri nets, equivalence proofs, formatters, latchers, neural simulators.

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