Global stabilization of memristor-based fractional-order neural networks with delay via output-feedback control

摘要

In this paper, the memristor-based fractional-order neural networks (MFNN) with delay and with two types of stabilizing control are described in detail. Based on the Lyapunov directmethod,thetheoriesofset-value maps, differential inclusions and comparison principle, some sufficient conditions and assumptions for globalstabilization of this neural network model are established. Finally, two numerical examples are presented to demonstrate the effectiveness and practicability of the obtained results.