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    ARTICLE

    Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

    Tianyuan Jia1, Xiangyong Chen1,2,*, Xiurong Yao1,*, Feng Zhao1, Jianlong Qiu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 221-239, 2023, DOI:10.32604/cmes.2022.020780

    Abstract Fixed-time synchronization (FTS) of delayed memristor-based neural networks (MNNs) with discontinuous activations is studied in this paper. Both continuous and discontinuous activations are considered for MNNs. And the mixed delays which are closer to reality are taken into the system. Besides, two kinds of control schemes are proposed, including feedback and adaptive control strategies. Based on some lemmas, mathematical inequalities and the designed controllers, a few synchronization criteria are acquired. Moreover, the upper bound of settling time (ST) which is independent of the initial values is given. Finally, the feasibility of our theory is attested by simulation examples. More >

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