ABSTRACT This paper investigates the problem of master-slave synchronization of neural networks with time-varying delays via the event-triggered control (ETC). First, the proposed ETC can effectively reduce the total amount of data transmitted to the controller in the synchronization process and avoid communication channel congestion. Second, a master-slave synchronization of neural networks with time-varying delays is constructed, where delays within neural networks and the ETC are simultaneous existence. The controller is updated by the ETC. By the Lyapunov stability theory, some sufficient criteria are obtained to ensure master-slave synchronization of neural networks. Finally, a numerical example and a tunnel diode circuit example are used to verify the validity of results obtained.

中文翻译：

---

通过事件触发控制具有时变延迟的神经网络的主从同步

摘要 本文通过事件触发控制 (ETC) 研究了具有时变延迟的神经网络的主从同步问题。首先，所提出的ETC可以有效减少同步过程中传输到控制器的数据总量，避免通信信道拥塞。其次，构建了具有时变延迟的神经网络的主从同步，其中神经网络内的延迟和 ETC 是同时存在的。控制器由 ETC 更新。通过李雅普诺夫稳定性理论，得到了一些充分的准则来保证神经网络的主从同步。最后，通过一个数值例子和一个隧道二极管电路例子来验证所得结果的有效性。