Finite-Time Dissipative Synchronization for Markovian Jump Generalized Inertial Neural Networks with Reaction-Diffusion Terms

Xiaona Song, Jingtao Man, Choon Ki Ahn, Shuai Song

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

A novel generalized neural network (NN), which includes Markovian jump parameters, inertial items, and reaction-diffusion terms, is proposed, and the issue of finite-time dissipative synchronization for this kind of NNs is discussed in this article. First, an appropriate variable substitution is employed so that the original second-order differential system is transformed into a first-order one. Second, a novel time-varying memory-based controller is designed to ensure the dissipative synchronization of the drive and response systems over a finite-time interval. Then, a new Lyapunov-Krasovskii function is processed by reciprocally convex combination and free-weighting matrix methods, therefore, a less conservative synchronization criterion is derived. Finally, by providing three examples, the feasibility, superiority, and practicality of the obtained results are illustrated.

Original languageEnglish
Article number8944299
Pages (from-to)3650-3661
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number6
DOIs
Publication statusPublished - 2021 Jun
Externally publishedYes

Keywords

  • Finite-time dissipative synchronization
  • Markovian jump parameters
  • generalized inertial neural networks (GINNs)
  • reaction-diffusion terms
  • time-varying memory-based controller

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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