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        Synchronization of inertial memristive neural networks with time-varying delays via static or dynamic event-triggered control

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        Neurocomputing_3.pdf (PDF, 1Mb)
        Author
        Yao, Wei
        Wang, Chunhua
        Sun, Yichuang
        Zhou, Chao
        Lin, Hairong
        Attention
        2299/22696
        Abstract
        This paper investigates the synchronization problem of inertial memristive neural networks (IMNNs) with time-varying delays via event-triggered control (ETC) scheme and state feedback controller for the first time. First, two types of state feedback controllers are designed; the first type of controller is added to the transformational first-order system, and the second type of controller is added to the original second-order system. Next, based on each feedback controller, static event-triggered control (SETC) condition and dynamic event-triggered control (DETC) condition are presented to significantly reduce the update times of controller and decrease the computing cost. Then, some sufficient conditions are given such that synchronization of IMNNs with time-varying delays can be achieved under ETC schemes. Finally, a numerical simulation and some data analyses are given to verify the validity of the proposed results.
        Publication date
        2020-09-03
        Published in
        Neurocomputing
        Published version
        https://doi.org/10.1016/j.neucom.2020.04.099
        Other links
        http://hdl.handle.net/2299/22696
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