Skip to main navigation Skip to search Skip to main content

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
Pages353-357
Number of pages5
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011 - Shanghai, China
Duration: 10 Jun 201112 Jun 2011

Publication series

NameProceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
Volume3

Conference

Conference2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011
Country/TerritoryChina
CityShanghai
Period10/06/1112/06/11

Keywords

  • artificial neural network
  • complex network
  • small-world network

Fingerprint

Dive into the research topics of 'A new multilayer feedforward small-world neural network with its performances on function approximation'. Together they form a unique fingerprint.

Cite this