Robust passivity analysis for neutral-type neural networks with mixed and leakage delays

Abstract

This paper investigates the problem of passivity of neutral-type neural networks with mixed and leakage delays. By establishing a suitable augmented Lyapunov functional and combining a new integral inequality with the reciprocally convex combination technique, we obtain some sufficient passivity conditions, which are formulated in terms of linear matrix inequalities (LMIs). Here, some useful information on the neuron activation function ignored in the existing literature is taken into account. Finally, some numerical examples are given to demonstrate the effectiveness of the proposed method.