State estimation for neural networks with multiple time delays

Abstract

The problem of state estimation for neural networks with leakage, discrete and distributed delays is investigated in this paper. Together with some new Lyapunov–Krasovskii functionals, convex polyhedron method and new activation function conditions, several sufficient conditions are derived. Some improved conditions are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Numerical examples are given to illustrate the effectiveness of the proposed methods.