Please use this identifier to cite or link to this item: https://oar.tib.eu/jspui/handle/123456789/5117
Title: Synchronization of a Class of Memristive Stochastic Bidirectional Associative Memory Neural Networks with Mixed Time-Varying Delays via Sampled-Data Control
Authors: Yuan, M.Wang, W.Luo, X.Ge, C.Li, L.Kurths, J.Zhao, W.
Publishers Version: https://doi.org/10.1155/2018/9126183
Issue Date: 2018
Published in: Mathematical Problems in Engineering Vol. 2018 (2018)
Publisher: London : Hindawi Limited
Abstract: The paper addresses the issue of synchronization of memristive bidirectional associative memory neural networks (MBAMNNs) with mixed time-varying delays and stochastic perturbation via a sampled-data controller. First, we propose a new model of MBAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying distributed delays and discrete delays. Second, we design a new method of sampled-data control for the stochastic MBAMNNs. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the methods are carefully designed to confirm the synchronization processes are suitable for the feather of the memristor. Third, sufficient criteria guaranteeing the synchronization of the systems are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.
Keywords: Associative processing; Associative storage; Memory architecture; Neural networks; Stochastic systems; Synchronization; Time delay; Time varying networks; Bi-directional associative memory neural networks; Distributed delays; Mixed time-varying delays; Numerical experiments; Sampled-data control; Sampled-data controller; Stochastic perturbations; Synchronization process; Time varying control systems
DDC: 510
License: CC BY 4.0 Unported
Link to License: https://creativecommons.org/licenses/by/4.0/
Appears in Collections:Mathematik



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