Exponential synchronization of chaotic neural networks with time-varying delay via intermittent output feedback approach

Zhi Ming Zhang, Yong He, Min Wu, Qing Guo Wang

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

This paper is dealt with the problem of exponential synchronization for chaotic neural networks with time-varying delay by using intermittent output feedback control. Based on the Lyapunov–Krasovskii functional method and the lower bound lemma for reciprocally convex technique, a novel criterion for existence of the controller is first established to ensure synchronization between the master and slave systems. Moreover, from the delay point of view, the derived criterion is extended to the relaxed case because of introducing an adjustable parameter in the Lyapunov–Krasovskii functional. Finally, a numerical simulation is carried out to demonstrate the effectiveness of the proposed synchronization law.

Original languageEnglish
Pages (from-to)121-132
Number of pages12
JournalApplied Mathematics and Computation
Volume314
DOIs
Publication statusPublished - 1 Dec 2017

Keywords

  • Exponential synchronization
  • Intermittent output feedback control
  • Lyapunov–Krasovskii functional
  • Neural networks
  • Time-varying delay

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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