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Intermittent control for synchronization of hybrid multi-weighted complex networks with reaction-diffusion effects

  • Beibei Guo*
  • , Yu Xiao
  • *Corresponding author for this work
  • Hebei Normal University
  • Hebei International Joint Research Center for Mathematics and Interdisciplinary Science
  • Hebei Key Laboratory of Computational Mathematics and Applications

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, exponential synchronization for hybrid multi-weighted complex networks is studied via aperiodically intermittent control. Different from previous work, both Markov jump and reaction-diffusion effects are simultaneously considered into multi-weighted complex networks. By employing network split technique, graph theory, and Lyapunov method, several synchronization criteria are derived. These criteria show the effects of multiple weights, Markov jump, and reaction-diffusion on exponential synchronization. Furthermore, an application to Cohen–Grossberg neural networks is conducted, and the corresponding synchronization criterion is given. Finally, some numerical simulations are presented to show the effectiveness of the obtained theoretical results.

Original languageEnglish
Pages (from-to)1137-1155
Number of pages19
JournalMathematical Methods in the Applied Sciences
Volume46
Issue number1
DOIs
StatePublished - 15 Jan 2023

Keywords

  • Cohen–Grossberg neural networks
  • aperiodically intermittent control
  • exponential synchronization
  • multi-weighted complex networks
  • reaction-diffusion

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