Finite-time synchronization of coupled Cohen-Grossberg neural networks with time-varying delays

  • Shui Han Qiu
  • , Yan Li Huang*
  • , Jin Liang Wang
  • , Shun Yan Ren
  • , Dong Fang Liu
  • *Corresponding author for this work

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

Abstract

This paper is concerned with finite-time synchronization for two models of coupled Cohen-Grossberg neural networks with time-varying delays. In the first one, linearly coupled Cohen-Grossberg neural networks is considered. In the second one, nonlinearly coupled Cohen-Grossberg neural networks is discussed. Based on finite-time stability theory, some inequality techniques, and designed controllers, some criteria which make the coupled Cohen-Grossberg neural networks with linear coupling and nonlinear coupling realize synchronization are derived respectively. Furthermore, the settling times of synchronization are also estimated. Finally, a numerical example is given to confirm the effectiveness of the proposed results.

Original languageEnglish
Title of host publicationProceedings of the 36th Chinese Control Conference, CCC 2017
EditorsTao Liu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages3966-3971
Number of pages6
ISBN (Electronic)9789881563934
DOIs
StatePublished - 7 Sep 2017
Externally publishedYes
Event36th Chinese Control Conference, CCC 2017 - Dalian, China
Duration: 26 Jul 201728 Jul 2017

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference36th Chinese Control Conference, CCC 2017
Country/TerritoryChina
CityDalian
Period26/07/1728/07/17

Keywords

  • Coupled Cohen-Grossberg neural networks
  • Finite-time synchronization
  • Linear coupling
  • Nonlinear coupling
  • Time-varying delays

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