In this paper, we mainly investigate global exponential synchronization for master-slave complex-valued neural networks (CVNNs) under a time-scale impulsive strategy. CVNNs are separated into real and imaginary parts, which lead to two real-valued neural networks (RVNNs). Firstly, impulsive Halanay differential inequality on time scales as well as the comparison between general exponential function and exponential function in timescale sense is given based on the calculus of time scales. Then by constructing the appropriate Lyapunov functional and using the established lemma and proposition, the concepts of average impulsive interval (AII) and average impulsive gain (AIG), some novel synchronization criteria for the given master-slave CVNNs in impulsive form are obtained. Additionally, the convergence rate is estimated explicitly. Finally, one numerical example is given to show the effectiveness of the proposed results.

中文翻译：

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CVNN的同步：时标脉冲策略

在本文中，我们主要研究在时标脉冲策略下的主-从复值神经网络（CVNN）的全局指数同步。CVNN分为实部和虚部，这导致了两个实值神经网络（RVNN）。首先，基于时标的微分，给出了时标上的脉冲Halanay微分不等式，以及时标意义上的一般指数函数和指数函数之间的比较。然后，通过构造适当的Lyapunov函数，并使用已建立的引理和命题，平均脉冲间隔（AII）和平均脉冲增益（AIG）的概念，获得了给定脉冲形式给定主从CVNN的一些新颖同步准则。此外，收敛速度是明确估计的。最后，