Passivity analysis of neural networks with discrete and distributed delays

This study is concerned with the problem of delay-dependent passivity analysis for neural networks with discrete and distributed delays. By employing a new integral inequality and the convex combination approach to estimate the derivative of Lyapunov-Krasovskii functional, sufficient conditions are established to ensure that the considered neural network is passive. A given numerical example demonstrates the effectiveness of the proposed method.