Global uniform asymptotic stability and synchronization for fractional-order BAM neural networks with time delays

In this article, a fractional-order bidirectional associative memory neural networks with time delays is investigated. Firstly, some criteria are established ensuring globally uniformly asymptotically stable for neural networks by applying the novel fractional Lyapunov method and Razumikhin-type theorem. Next, the synchronization of fractional-order neural networks is also proposed. Finally, an numerical simulation is presented to verify the validity of the obtained results.