Synchronization of memristor-based delayed BAM neural networks with fractional-order derivatives

Abstract

This article deals with the problem of synchronization of fractional-order memristor-based BAM neural networks (FMBNNs) with time-delay. We investigate the sufficient conditions for adaptive synchronization of FMBNNs with fractional-order 0 < α < 1. The analysis is based on suitable Lyapunov functional, differential inclusions theory, and master-slave synchronization setup. We extend the analysis to provide some useful criteria to ensure the finite-time synchronization of FMBNNs with fractional-order 1 < α < 2, using Mittag-Leffler functions, Laplace transform, and linear feedback control techniques. Numerical simulations with two numerical examples are given to validate our theoretical results. Presence of time-delay and fractional-order in the model shows interesting dynamics. © 2016 Wiley Periodicals, Inc. Complexity, 2016