Neural simulation of Petri nets

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

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

2 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)183-207
頁數25
期刊Parallel Computing
25
發行號2
DOIs
出版狀態已發佈 - 1999 一月 1

ASJC Scopus subject areas

  • 軟體
  • 理論電腦科學
  • 硬體和架構
  • 電腦網路與通信
  • 電腦繪圖與電腦輔助設計
  • 人工智慧

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