基于忆阻的时变时滞神经网络的自适应同步

Adaptive Synchronization of Memristor-based Chaotic Neural Networks with Time-varying Delays

本文研究一类基于忆阻的混沌时变时滞神经网络的驱动-响应同步控制.根据忆阻器依赖状态转换的特性,将误差系统分为四种情况,能够使得所研究的模型实现全局渐近同步的自适应控制器被构造,而且,不需要通过解任何不等式或矩阵不等式,所设计的自适应控制器就能够实现.最后,给出一个数值算例验证了本文理论结果的有效性.

This paper investigates drive-response synchronization of a class of memristor-based chaotic neural networks withtime-varying delays. Based on the state-dependent switching feature of memristor, the error system is divided into four cases.Theadaptive controller is designed so that the considered model can realize globally asymptotical synchronization. Moreover, the designof adaptive controller is easily achieved without solving any inequality or linear matrix inequality. Finally, a numerical simulation isgiven to verify the effectiveness of the theoretical results.