Mittag-Leffler stability analysis on variable-time impulsive fractional-order neural networks

Mittag-Leffler stability analysis of fractional-order neural networks with variable-time impulses is addressed in this paper. Several well-proposed conditions with theoretical demohstration ensuring that every solution of concerned models intersects each surface of the discontinuities exactly once are provided. Meanwhile, by applying B-equivalence method, the reduced fractional-order neural networks with fixed-time impulsive effects can be regarded as the comparison systems of the investigated original network models. Furthermore, a series of sufficient criteria illustrating the same stability properties between both variable-time impulsive fractional-order neural networks and the fixed-time alternative, and guaranteeing the stability of the considered models are presented. Finally, two simulation examples are presented to demonstrate the efficiency and feasibility of the achieved results. (C) 2016 Elsevier B.V. All rights reserved.