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A new multilayer feedforward small-world neural network with its performances on function approximation

  • Xiaohu Li
  • , Xiaoling Li
  • , Jinhua Zhang
  • , Yulin Zhang
  • , Maolin Li
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

14 引用 (Scopus)

摘要

In this paper, by the use of the research results from complex network, a new multilayer feedforward small-world neural network is presented. Firstly, based on the construction ideology of Watts-Strogatz network model and community structure, a new multilayer feedforward small-world neural network is built up, which heavily relies on the rewiring probability. Secondly, the network model is briefly described by mathematical method. Finally, in order to investigate the performances of new small-world neural network, function approximation and fault tolerance are used to test the network performances. Simulation results show that the new neural network has the best approximate performance when the rewiring probability is nearby 0.1, and the approximate speed comparison also shows that small-world neural network is superior to regular network and random network at this time.

源语言英语
主期刊名Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
353-357
页数5
DOI
出版状态已出版 - 2011
活动2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011 - Shanghai, 中国
期限: 10 6月 201112 6月 2011

出版系列

姓名Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
3

会议

会议2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
国家/地区中国
Shanghai
时期10/06/1112/06/11

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