New stability results for delayed neural networks

摘要

This paper is concerned with the stability for delayed neural networks. By more fully making use of the information of the activation function, a new Lyapunov–Krasovskii functional (LKF) is constructed. Then a new integral inequality is developed, and more information of the activation function is taken into account when the derivative of the LKF is estimated. By Lyapunov stability theory, a new stability result is obtained. Finally, three examples are given to illustrate the stability result is less conservative than some recently reported ones.