%A M. Syed Ali, R. Saravanakumar
%T Augmented Lyapunov approach to H∞ state estimation of static neural networks with discrete and distributed time-varying delays
%0 Journal Article
%D 2015
%J Chin. Phys. B
%R 10.1088/1674-1056/24/5/050201
%P 50201-050201
%V 24
%N 5
%U {https://cpb.iphy.ac.cn/CN/abstract/article_117380.shtml}
%8 2015-05-05
%X 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.