Robust Exponential Synchronization for Memristor Neural Networks with Nonidentical Characteristics by Pinning Control

Yueheng Li, Biao Luo*, Derong Liu, Yin Yang, Zhanyu Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

In this paper, robust exponential synchronization of memristor-based neural networks (MNNs) with nonidentical characteristics is investigated. Coefficient mismatch, time-varying delay mismatch, and activation function mismatch are considered between the drive and the response MNNs. Pinning control strategy is developed to realize robust exponential synchronization and the stability criteria is established by using the Lyapunov function method and differential inclusion theory. Furthermore, the stable region of controller parameters is computed to guarantee that the synchronization errors enter a predetermined error bound within given settling time. Finally, the effectiveness of the proposed methods is verified by the numerical simulations. The methods presented in this paper offer novel schemes for robust exponential synchronization of nonidentical MNNs.

Original languageEnglish
Article number8701564
Pages (from-to)1966-1980
Number of pages15
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number3
DOIs
Publication statusPublished - Mar 2021

Keywords

  • Error bound
  • exponential synchronization
  • memristor-based neural networks (MNNs)
  • nonidentical characteristics
  • pinning control
  • stable region

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