This brief investigates the master-slave synchronization problem of delayed neural networks with general time-varying control. Assuming a linear feedback controller with time-varying control gain, the synchronization problem is recast into the stability problem of a delayed system with a time-varying coefficient. The main theorem is established in terms of the time average of the control gain by using the Lyapunov-Razumikhin theorem. Moreover, the proposed framework encompasses some general intermittent control schemes, such as the switched control gain with external disturbance and intermittent control with pulse-modulated gain function, while some useful corollaries are consequently deduced. Interestingly, our theorem also provides a solution for regaining stability under control failure. The validity of the theorem and corollaries is further demonstrated with numerical examples.

中文翻译：

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具有时变控制的延迟神经网络的主从同步。

本简介研究了具有一般时变控制的延迟神经网络的主从同步问题。假设一个具有时变控制增益的线性反馈控制器，同步问题被重新转化为具有时变系数的延迟系统的稳定性问题。利用Lyapunov-Razumikhin定理，根据控制增益的时间平均值建立主定理。此外，所提出的框架包含一些通用的间歇控制方案，例如具有外部干扰的开关控制增益和具有脉冲调制增益函数的间歇控制，同时推导出一些有用的推论。有趣的是，我们的定理还提供了一种在控制失败的情况下恢复稳定性的解决方案。