Stability analysis of memristor-based time-delay fractional-order neural networks.

In this paper, a class of memristor-based time-delay fractional-order neural networks has been investigated. Through constructing Lyapunov functional and applying the Gronwall’s integral inequality, new criteria to guarantee the global Mittag–Leffler stability have been proposed for the addressed neural networks. At the same time, by employing contraction mapping principle, sufficient conditions for ensuring the existence and uniqueness of the equilibrium point are also presented. Numerical examples are given to illustrate the effectivity and feasibility of our results.