New stability conditions of delayed neural networks via improved Lyapunov-Krasovskii functionals

This paper studies the delay-dependent stability problems of neural networks with time-delays. Firstly, in order to make the constructed function contain more useful information, this paper introduces three types of Lyapunov-Krasovskii functional terms to construct an improved Lyapunov-Krasovskii functional. Then, based on the improved Lyapunov-Krasovskii functional and reciprocal convex integral inequalities, some less conservative stability criteria are derived for the considered neural networks. Finally, a well-known numerical example is provided to demonstrate the superiority of the proposed stability criteria.