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Dynamical Analysis of a Tri-Neuron Fractional Network

  • Cheng Dai Huang
  • , Jin De Cao
  • , Min Xiao
  • , Ahmed Alsaedi
  • , Fuad E. Alsaadi
  • , Tasawar Hayat
  • Southeast University, Nanjing
  • Hubei University of Arts and Science
  • Shandong Normal University
  • Nanjing University of Posts and Telecommunications
  • King Abdulaziz University
  • Faculty of Engineering, King Abdulaziz University
  • Faculty of Sciences, King Abdulaziz University
  • Quaid-I-Azam University

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The present paper concerns with the dynamics of a fractional neural network involving three neurons. Firstly, the bifurcation point is identified for which Hopf bifurcations may occur by taking the system parameter as a bifurcation parameter via the stability analysis of fractional systems. It is indicated that the system parameter can significantly affect the dynamical properties of such network. Secondly, the impact of the order on the bifurcation point is carefully examined. It is found that the occurrence of bifurcation is delayed as the order increases as long as the other system parameters are established. Finally, a numerical example is exploited to verify the efficiency of theoretical results.

Original languageEnglish
Pages (from-to)2042-2050
Number of pages9
JournalAsian Journal of Control
Volume19
Issue number6
DOIs
StatePublished - Nov 2017
Externally publishedYes

Keywords

  • Fractional order
  • Hopf bifurcation
  • neural networks
  • stability
  • system parameter

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