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Recent Advances on Dynamical Behaviors of Coupled Neural Networks with and without Reaction-Diffusion Terms

  • Tiangong University
  • Beijing Normal University
  • Harbin Institute of Technology
  • Texas A&M University at Qatar

Research output: Contribution to journalArticlepeer-review

Abstract

Recently, the dynamical behaviors of coupled neural networks (CNNs) with and without reaction-diffusion terms have been widely researched due to their successful applications in different fields. This article introduces some important and interesting results on this topic. First, synchronization, passivity, and stability analysis results for various CNNs with and without reaction-diffusion terms are summarized, including the results for impulsive, time-varying, time-invariant, uncertain, fuzzy, and stochastic network models. In addition, some control methods, such as sampled-data control, pinning control, impulsive control, state feedback control, and adaptive control, have been used to realize the desired dynamical behaviors in CNNs with and without reaction-diffusion terms. In this article, these methods are summarized. Finally, some challenging and interesting problems deserving of further investigation are discussed.

Original languageEnglish
Article number9037199
Pages (from-to)5231-5244
Number of pages14
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume31
Issue number12
DOIs
StatePublished - Dec 2020

Keywords

  • Coupled neural networks (CNNs)
  • coupled reaction-diffusion neural networks
  • passivity
  • stability
  • synchronization

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