A novel fixed-time stability strategy and its application to fixed-time synchronization control of semi-Markov jump delayed neural networks

摘要

This paper emphasizes on a novel fixed-time stability strategy and its application to fixed-time synchro-nization control for a class of semi-Markov jump delayed Cohen-Grossberg neural networks (SMJDCGNNs). First, a novel fixed-time stability strategy for a class of nonlinear delayed systems is pro-posed, which is a generalization of the existing stability strategies. Second, the addressed fixed-time sta-bility strategy is applied to solving fixed-time synchronization control for a class of SMJDCGNNs, whose framework generalizes the existing Cohen-Grossberg neural networks (CGNNs). The application testifies that compared with the existing fixed-time stability strategies, the obtained fixed-time stability strategy can provide a tighter settling time which can more effectively and accurately estimate the convergence time of the studied delayed system. Finally, we give a comparative example to illustrate the validity of our results. (c) 2021 Elsevier B.V. All rights reserved.