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Bipartite and H bipartite synchronization for multiweighted coupled fractional-order delayed reaction-diffusion neural networks

  • Ya Nan Li
  • , Jin Liang Wang*
  • , Shun Yan Ren
  • , Tingwen Huang
  • *Corresponding author for this work
  • Tiangong University
  • Linyi University
  • Guangzhou Institute of Science and Technology
  • Shenzhen University of Advanced Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, two types of multiweighted coupled fractional-order delayed reaction-diffusion neural networks (MCFDRNN) with and without external disturbances under signed graph are introduced, which generalize the existing coupled fractional-order reaction-diffusion networks models. Several bipartite and H∞ bipartite synchronization conditions for these two MCFDRNN are given on the basis of some important lemmas and matrix theory, which can not be acquired by utilizing the method and technique used in coupled reaction-diffusion neural networks. Finally, the derived criteria are validated by exploiting a numerical example.

Original languageEnglish
Article number108863
JournalNeural Networks
Volume201
DOIs
StatePublished - Sep 2026
Externally publishedYes

Keywords

  • Bipartite synchronization
  • Coupled fractional-order delayed reaction-diffusion neural networks (CFDRNN)
  • Hbipartite synchronization
  • Multiple weights

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