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

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 45; no. 7; pp. 1077 - 1086
• Main Authors: Yang, Shaofu, Guo, Zhenyuan, Wang, Jun
• Format: Journal Article
• Language: English
• Published: IEEE 01-07-2015
• Subjects: Biological neural networks; Couplings; Global robust synchronization; Manganese; memristive neural networks (MNNs); Multi-layer neural network; nonlinear coupling; pinning adaptive coupling; Robustness; Synchronization; Uncertain systems; memristive neural networks (MNNs); pinning adaptive coupling; nonlinear coupling; Global robust synchronization
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2014.2388199

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.