4.7 Article

Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control

Journal

NEURAL NETWORKS
Volume 119, Issue -, Pages 178-189

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2019.08.011

Keywords

Memristive neural networks; Synchronization; Parameters mismatch; Leakage delay

Funding

  1. Natural Science Foundation of China [61673187]
  2. Shenzhen Innovative Grant from Research Institute in Shenzhen, Huazhong University of Science and Technology [JCYJ20170307160806070]
  3. NPRP from Qatar National Research Fund (a member of Qatar Foundation) [NPRP 8-274-2-107]

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In this paper, we investigate the synchronization problem on delayed memristive neural networks (MNNs) with leakage delay and parameters mismatch via event-triggered control. We divide MNNs with parameters mismatch into two categories for discussion. One is state-dependent and can achieve synchronization by designing a suitable controller. A novel Lyapunov functional is constructed to analyze the synchronization problem. Moreover, the triggering conditions are independent from the delay boundaries and can be static or dynamic. Another category of parameters mismatch is structure-dependent and can only achieve quasi-synchronization by appropriate controller. By using matrix measure method and generalized Halanay inequality, a quasi-synchronization criterion is established. The controllers in this paper are discrete state-dependent and can be updated under the event-based triggering condition, which is more simpler than the previous results. In the end of our paper, two illustrative examples are given to support our results. (C) 2019 Elsevier Ltd. All rights reserved.

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