Li Ning, Cao Jinde
Department of Mathematics, and Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing 210096, Jiangsu, China.
Department of Mathematics, and Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing 210096, Jiangsu, China; Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Neural Netw. 2015 Jan;61:1-9. doi: 10.1016/j.neunet.2014.08.015. Epub 2014 Sep 8.
In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results.
在本文中，我们通过自适应和反馈控制器研究具有时变延迟的忆阻器神经网络的同步问题。在菲利波夫解和微分包含理论的框架下，利用自适应控制技术并构造一个新颖的李雅普诺夫泛函，设计了一种自适应更新律，并推导了具有时变延迟的忆阻器神经网络的两个同步准则。通过去除一些基本文献假设，发现所推导的同步准则比现有文献中的准则更具一般性。最后，给出两个仿真例子来说明理论结果的有效性。
