Robust Synchronization of Multiple Memristive Neural Networks With Uncertain Parameters via Nonlinear Coupling
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AbstractThis 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.
All Author(s) ListYang SF, Guo ZY, Wang J
Journal nameIEEE Transactions on Systems Man and Cybernetics: Systems
Year2015
Month7
Day1
Volume Number45
Issue Number7
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Pages1077 - 1086
ISSN2168-2216
LanguagesEnglish-United Kingdom
KeywordsGlobal robust synchronization; memristive neural networks (MNNs); nonlinear coupling; pinning adaptive coupling
Web of Science Subject CategoriesAutomation & Control Systems; Computer Science; Computer Science, Cybernetics

Last updated on 2020-25-11 at 03:11