Complete Periodic Synchronization of Memristor-Based Neural Networks with Time-Varying Delays
Huaiqin Wu, Luying Zhang, Sanbo Ding, Xueqing Guo, Lingling Wang · Discrete Dynamics in Nature and Society · 2013
This paper investigates the complete periodic synchronization of memristor-based neural networks with time-varying delays. Firstly, under the framework of Filippov solutions, by usingM-matrix theory and the Mawhin-like coincidence theorem in set-valued analysis, the existence of the periodic solution for the network system is proved. Secondly, complete periodic synchronization is considered for memristor-based neural networks. According to the state-dependent switching feature of the memristor, the error system is divided into four cases. Adaptive controller is designed such that the considered model can realize global asymptotical synchronization. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.