Finite-time Synchronization of Inertial Neural Networks via Periodically Intermittent Control

Yaqian Hu, Leimin Wang, Xingxing Tan, Kan Zeng
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Abstract

In this paper, the finite-time synchronization (FTS) for inertial neural networks (INNs) is investigated based on periodically intermittent control. By utilizing the reduced order approach, INN system is transformed into two first-order systems. Then, proper periodically intermittent controllers are designed to obtain sufficient condition for FTS of INNs. An example is proposed to support the validity of the synchronization criterion.
基于周期性间歇控制的惯性神经网络有限时间同步
研究了基于周期性间歇控制的惯性神经网络的有限时间同步问题。利用降阶方法,将INN系统转化为两个一阶系统。然后,设计了合适的周期间歇控制器,以获得惯性神经网络时域变换的充分条件。通过实例验证了同步准则的有效性。
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