Augmented Lyapunov approach to H∞ state estimation of static neural networks with discrete and distributed time-varying delays**Project supported by the Fund from National Board of Higher Mathematics (NBHM), New Delhi (Grant No. 2/48/10/2011-R&D-II/865).

Abstract

This paper deals with H∞ state estimation problem of neural networks with discrete and distributed time-varying delays. A novel delay-dependent concept of H∞ state estimation is proposed to estimate the H∞ performance and global asymptotic stability of the concerned neural networks. By constructing the Lyapunov–Krasovskii functional and using the linear matrix inequality technique, sufficient conditions for delay-dependent H∞ performances are obtained, which can be easily solved by some standard numerical algorithms. Finally, numerical examples are given to illustrate the usefulness and effectiveness of the proposed theoretical results.