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Title: Neural simulation of Petri nets
Authors: 國立臺灣師範大學資訊教育研究所
Chen, S. W.
Fang, C. Y.
Chang, K. E.
Issue Date: 1-Feb-1999
Publisher: Elsevier
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.
ISSN: 0167-8191
Other Identifiers: ntnulib_tp_A0904_01_029
Appears in Collections:教師著作

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