College of Mathematics and Econometrics, Hunan University, Changsha, 410082, China.
School of Automation and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, China.
Neural Netw. 2019 Nov;119:178-189. doi: 10.1016/j.neunet.2019.08.011. Epub 2019 Aug 20.
In this paper, we investigate the synchronization problem on delayed memristive neural networks (MNNs) with leakage delay and parameters mismatch via event-triggered control. We divide MNNs with parameters mismatch into two categories for discussion. One is state-dependent and can achieve synchronization by designing a suitable controller. A novel Lyapunov functional is constructed to analyze the synchronization problem. Moreover, the triggering conditions are independent from the delay boundaries and can be static or dynamic. Another category of parameters mismatch is structure-dependent and can only achieve quasi-synchronization by appropriate controller. By using matrix measure method and generalized Halanay inequality, a quasi-synchronization criterion is established. The controllers in this paper are discrete state-dependent and can be updated under the event-based triggering condition, which is more simpler than the previous results. In the end of our paper, two illustrative examples are given to support our results.
本文研究了具有时滞和参数失配的忆阻神经网络（MNN）的同步问题，采用事件触发控制。我们将参数失配的 MNN 分为两类进行讨论。一类是状态依赖的，可以通过设计合适的控制器实现同步。构造了一个新的李雅普诺夫函数来分析同步问题。此外，触发条件与延迟边界无关，可以是静态的也可以是动态的。参数失配的另一类是结构依赖的，只能通过适当的控制器实现准同步。利用矩阵测度法和广义 Halanay 不等式，建立了准同步准则。本文中的控制器是离散状态依赖的，可以在基于事件的触发条件下更新，比以前的结果更简单。最后，给出了两个实例来说明我们的结果。
