This paper investigates the problem of global $\mu$-synchronization of impulsive pantograph neural networks. In this paper, new concept of $\nu$-asymptotic periodic impulsive interval $T_{asy}^{\nu }$ is proposed for pantograph networks. By employing the Lyapunov method combined with the mathematical analysis approach for impulsive systems, some useful criteria are derived to guarantee the global $\mu$-synchronization of coupled pantograph neural networks when the asymptotic logarithmic periodic impulsive interval $T_{asy}^{ln}<\infty$ and $T_{asy}^{ln}=\infty$, respectively. Especially when $T_{asy}^{ln}=\infty$, as long as the networks are unstable, impulsive control cannot achieve synchronization regardless of the size of the impulse gain. Numerical simulations are exploited to illustrate our theoretical results.

本文研究了全球性问题 $\mu$脉冲受电弓神经网络的同步。本文中的新概念$\nu$渐近周期脉冲间隔 ${Ť}_{\mathrm{一种}sÿ}^{\nu }$被提议用于受电弓网络。通过将Lyapunov方法与数学分析方法结合用于脉冲系统，得出了一些有用的准则来保证整体性$\mu$渐近对数周期脉冲区间的受电弓神经网络同步 ${Ť}_{\mathrm{一种}sÿ}^{ln}<\infty$ 和 ${Ť}_{\mathrm{一种}sÿ}^{ln}=\infty$， 分别。特别是当${Ť}_{\mathrm{一种}sÿ}^{ln}=\infty$只要网络不稳定，无论脉冲增益的大小如何，脉冲控制都无法实现同步。数值模拟被用来说明我们的理论结果。