Exponential synchronisation of linearly coupled reaction-diffusion neural networks with discrete and infinite distributed delays

Ping He, Heng Li, Xiaochun Luo, Mali Xing

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

This paper presents the exponential synchronisation for linearly coupled reaction-diffusion neural networks (CRDNNs) with discrete, infinite distributed delays and Dirichlet boundary condition. Two sufficient criteria are obtained for the exponential synchronisation of linearly coupled semi-linear diffusion partial differential equations (PDEs) with discrete, infinite distributed time-delays by using the Halanay inequality and Lyapunov-Krasoviskii functional stability scheme. These results are presented by linear matrix inequality and solved by MATLAB LMI Toolbox. Two simulation examples of linearly CRDNNs with discrete, infinite distributed delays are given to illustrate the validity of the results obtained above.

Original languageEnglish
Pages (from-to)1174-1187
Number of pages14
JournalInternational Journal of Systems Science
Volume51
Issue number7
DOIs
Publication statusPublished - 18 May 2020

Keywords

  • Coupled reaction-diffusion neural networks
  • exponential synchronisation
  • infinite distributed delay
  • linear matrix inequality
  • partial differential system

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications

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