College of Science, China Three Gorges University, Yichang, Hubei 443002, China.
Centre of New Energy Systems, Department of Electrical and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa.
Neural Netw. 2015 Mar;63:133-40. doi: 10.1016/j.neunet.2014.11.005. Epub 2014 Nov 27.
This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient conditions for finite-time synchronization between the master and corresponding slave memristor-based neural network with the designed controller. In comparison with the existing results, the proposed stability conditions are new, and the obtained results extend some previous works on conventional recurrent neural networks. Two numerical examples are provided to illustrate the effective of the design method.
本文提出了一种用于忆阻器神经网络的全局和局部有限时间同步控制律。通过利用驱动-响应概念、微分包含理论和李雅普诺夫函数方法，我们为带有设计控制器的主从忆阻神经网络之间的有限时间同步建立了几个充分条件。与现有结果相比，所提出的稳定性条件是新颖的，所得到的结果扩展了一些关于常规递归神经网络的已有工作。给出了两个数值示例来说明设计方法的有效性。
