%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.