General decay projective synchronization of drive-response reaction-diffusion memristive neural networks

Xin Zhao, Yanli Huang, Tse Chiu Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

This paper studies the general decay projective synchronization (GDPS) of a class of drive-response reaction-diffusion memristive neural networks (RDMNNs). Firstly, a suitable controller is designed, which does not ask for any knowledge about the activation functions. Then we investigate the GDPS of drive-response RDMNNs by constructing a suitable Lyapunov functional, and an adequate condition for guaranteeing the GDPS of this type of network is inferred. Lastly, the validity of the result is demonstrated by one numerical example with simulation results.
Original languageEnglish
Title of host publication2023 IEEE 13th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1253-1257
Number of pages5
ISBN (Electronic)9798350315196
ISBN (Print)9798350315202
DOIs
Publication statusPublished - 28 Sept 2023

Publication series

NameIEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
PublisherIEEE
ISSN (Electronic)2642-6633

Keywords

  • general decay projective synchronization
  • drive-response reaction-diffusion memristive neural networks
  • RDMNNs
  • GDPS

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