On Stability Analysis for Generalized Neural Networks with Time-Varying Delays

Abstract EN

This paper deals with the problem of stability analysis for generalized neural networks with time-varying delays.

With a suitable Lyapunov-Krasovskii functional (LKF) and Wirtinger-based integral inequality, sufficient conditions for guaranteeing the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs).

By applying the proposed methods to two numerical examples which have been utilized in many works for checking the conservatism of stability criteria, it is shown that the obtained results are significantly improved comparing with the previous ones published in other literature.