Robust passivity analysis for stochastic impulsive neural networks with leakage and additive time-varying delay components

The purpose of this paper is to investigate the problem of robust passivity analysis for delayed stochastic impulsive neural networks with leakage and additive time-varying delays. The novel contribution of this paper lies in the consideration of a new integral inequality proved to be well-known Jensen's inequality and takes fully the relationship between the terms in the Leibniz-Newton formula within the framework of linear matrix inequalities (LMIs). By constructing a suitable Lyapunov-Krasovskii functional with triple and four integral terms using Jensen's inequality, integral inequality technique and LMI frame work, which guarantees stability for the passivity of addressed neural networks. This LMI can be easily solved via convex optimization techniques. Finally, two interesting numerical examples are given to show the effectiveness of the theoretical results.