Finite-Time Synchronization of Fractional-Order Quaternion-Valued Neural Networks under Aperiodically Intermittent Control: A Non-Separation Method

Xinlong Zhang
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Abstract

This article mainly focuses on investigating finite-time synchronization(FTS) of fractional-order quaternionvalued neural networks(FOQVNNs) with time-varying delay via aperiodically intermittent control. Firstly, a new group of fractional differential inequalities during aperiodically intermittent times is proposed, which provides a formula for calculating stable time \(\tilde{t}\) related to a parameter \(\varpi\) about aperiodically intermittent control strategy. It can make the stable time \(\tilde{t}\) even shorter than that of many existing literature results. Secondly, the theoretical analysis of the entire paper is conducted in a nonseparable method, and a quaternion-valued aperiodically intermittent controller based on 1-norm is directly designed to ensure the synchronization of FOQVNNs. By constructing a suitable Lyapunov function, the FTS criterion is derived. Finally, the validity of the proposed theoretical results is confirmed by numerical simulations.
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非周期间歇控制下分数阶四元数值神经网络的有限时间同步:一种非分离方法
本文主要通过非周期性间歇控制来研究具有时变延迟的分数阶四元值神经网络(FOQVNN)的有限时间同步(FTS)问题。首先,提出了一组新的非周期性间歇时间分数微分不等式,为计算与参数\(\varpi\)有关的非周期性间歇控制策略的稳定时间\(\tilde{t}\)提供了公式。它可以使稳定时间(\tilde{t}\)比许多现有文献结果的稳定时间(\tilde{t}\)更短。其次,整篇论文的理论分析都是以不可分割的方法进行的,并直接设计了一个基于 1-norm 的四元数值周期性间歇控制器来保证 FOQVNNs 的同步性。通过构建合适的 Lyapunov 函数,得出了 FTS 准则。最后,通过数值模拟证实了所提理论结果的正确性。
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