Global adaptive matrix-projective synchronization of delayed fractional-order competitive neural network with different time scales

Abstract

In this paper, by using the adaptive control method, the global matrix-projective synchronization of delayed fractional-order competitive neural network with different time scales is researched for the first time. Firstly, the fractional-order global matrix-projective synchronization is defined. Then, in order to achieve the matrix-projective synchronization, the sufficient condition is obtained under an adaptive controller and its effectiveness is proved by combining the fractional-order Barbalat theory with a suitable Lyapunov–Krasovskii functional as well as some fractional-order differential inequalities. And all unknown parameters are identified and estimated to the fixed constants successfully. Finally, as applications, a numerical example with simulations is employed to demonstrate the feasibility and efficiency of the new synchronization analysis.