This paper deals with the finite-time stabilization of fractional-order inertial neural network with varying time-delays (FOINNs). Firstly, by correctly selected variable substitution, the system is transformed into a first-order fractional differential equation. Secondly, by building Lyapunov functionalities and using analytical techniques, as well as new control algorithms (which include the delay-dependent and delay-free controller), novel and effective criteria are established to attain the finite-time stabilization of the addressed system. Finally, two examples are used to illustrate the effectiveness and feasibility of the obtained results.

中文翻译：

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具有时变延迟的分数阶惯性神经网络的有限时间稳定

本文讨论了具有不同时延（FOINN）的分数阶惯性神经网络的有限时间稳定性。首先，通过正确选择变量代入，将系统转化为一阶分数阶微分方程。其次，通过构建 Lyapunov 函数并使用分析技术以及新的控制算法（包括延迟相关和无延迟控制器），建立了新颖有效的标准，以实现所处理系统的有限时间稳定性。最后通过两个例子说明所得结果的有效性和可行性。