Robust Synchronization of Multiple Memristive Neural Networks with Uncertain Parameters via Nonlinear Coupling

Shaofu Yang, Zhenyuan Guo, Jun Wang

Research output: Contribution to journalArticlepeer-review

164 Citations (Scopus)

Abstract

This paper is concerned with the global robust synchronization of multiple memristive neural networks (MMNNs) with nonidentical uncertain parameters. A coupling scheme is introduced, in a general topological structure described by a direct or undirect graph, with a linear diffusive term and a discontinuous sign term. First, a set of sufficient conditions are derived based on the Lyapunov stability theory for ascertaining global robust synchronization of coupled MMNNs. Second, a pinning adaptive coupling method is proposed to ensure global synchronization without knowing the bound of parameter uncertainties. Two illustrative examples are discussed to substantiate the theoretical results.

Original languageEnglish
Article number7018050
Pages (from-to)1077-1086
Number of pages10
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume45
Issue number7
DOIs
Publication statusPublished - 1 Jul 2015
Externally publishedYes

Keywords

  • Global robust synchronization
  • memristive neural networks (MNNs)
  • nonlinear coupling
  • pinning adaptive coupling

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