Guo Zhenyuan, Gong Shuqing, Wen Shiping, Huang Tingwen
IEEE Trans Cybern. 2019 Sep;49(9):3268-3277. doi: 10.1109/TCYB.2018.2839686. Epub 2018 Jun 27.
In this paper, we investigate the global synchronization control problem for memristive neural networks (MNNs) with time-varying delay. A novel event-triggered controller is introduced with the linear diffusive term and discontinuous sign term. In order to greatly reduce the computation cost of the controller under certain event-triggering condition, two event-based control schemes are proposed with static event-triggering condition and dynamic event-triggering condition. Some sufficient conditions are derived by these control schemes to ensure the response MNN to be synchronized with the driving one. Furthermore, under certain event-triggering conditions, a positive lower bound is achieved for the interexecution time to guarantee that Zeno behavior cannot be executed. Finally, numerical simulations are provided to substantiate the effectiveness of the proposed theoretical results.
在本文中，我们研究了具有时变延迟的忆阻神经网络（MNNs）的全局同步控制问题。引入了一种带有线性扩散项和不连续符号项的新型事件触发控制器。为了在特定事件触发条件下大幅降低控制器的计算成本，提出了两种基于事件的控制方案，分别具有静态事件触发条件和动态事件触发条件。通过这些控制方案推导出了一些充分条件，以确保响应MNN与驱动MNN同步。此外，在特定事件触发条件下，执行间隔时间达到了一个正的下界，以保证不会出现芝诺行为。最后，通过数值模拟验证了所提理论结果的有效性。
