New Results on Synchronization of Fractional-Order Memristor‐Based Neural Networks via State Feedback Control
Xiaofan Li, Yuan Ge, Hongjian Liu, Huiyuan Li, Jian‐an Fang · Complexity · 2020
This paper addresses the synchronization issue for the drive-response fractional-order memristor‐based neural networks (FOMNNs) via state feedback control. To achieve the synchronization for considered drive-response FOMNNs, two feedback controllers are introduced. Then, by adopting nonsmooth analysis, fractional Lyapunov’s direct method, Young inequality, and fractional-order differential inclusions, several algebraic sufficient criteria are obtained for guaranteeing the synchronization of the drive-response FOMNNs. Lastly, for illustrating the effectiveness of the obtained theoretical results, an example is given.