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Fixed-Time and Preassigned-Time Synchronization of Delayed Inertial Neural Networks

机译:延迟惯性神经网络的固定时间和预测时间同步

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This paper investigates the fixed-time synchronization (FXTS) and the preassigned-time synchronization (PATS) of inertial neural networks (INNs) by improved control strategies. Firstly, using the order-reduce method, a proper Lyapunov function is constructed and a FXTS controller is designed. Then, some novel conditions for TXTS of INNs are derived and a more precise estimate for the settling time are provided. Moreover, depending on the FXTS, another PATS controller is proposed, with which the PATS of INNs is also achieved. Finally, the correctness and validity of the FXTS and PATS results are illustrated by a numerical example.
机译:本文通过改进的控制策略调查了定时同步(FXTS)和惯性神经网络(INN)的预测时间同步(PATS)。 首先,使用顺序减少方法,构造了适当的Lyapunov功能,设计了FXTS控制器。 然后,提供了一些用于徒点的TXTS的一些新颖的条件,并且提供了更精确的稳定时间估计。 此外,取决于FXTS,提出了另一个PATS控制器,也可以实现挪用的步骤。 最后,通过数值示例说明了FXTS和PATS结果的正确性和有效性。

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