On fractional variable-order neural networks with time-varying external inputs

Abstract

This research discuss the existence, uniqueness, asymptotic stability, and global asymptotic synchronization of a class of Caputo variable-order neural networks with time-varying external inputs. Theory of contraction mapping is used to establish a sufficient condition for determining the existence and uniqueness of the equilibrium point. Using the variable fractional Lyapunov approach, we investigate the asymptotic stability of the unique equilibrium. Synchronization of variable-order chaotic networks is also studied using an effective controller. Three numerical examples are provided to show the efficacy of the results obtained.