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Chin. Phys. B, 2015, Vol. 24(5): 050201    DOI: 10.1088/1674-1056/24/5/050201
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Augmented Lyapunov approach to H state estimation of static neural networks with discrete and distributed time-varying delays

M. Syed Ali, R. Saravanakumar
Department of Mathematics, Thiruvalluvar University, Vellore-632115, Tamil Nadu, India
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.
Keywords:  distributed delay      H state estimation      neural networks      stability analysis  
Received:  11 September 2014      Revised:  07 December 2014      Accepted manuscript online: 
PACS:  02.30.Hq (Ordinary differential equations)  
  02.30.Ks (Delay and functional equations)  
  05.45.-a (Nonlinear dynamics and chaos)  
  02.10.Yn (Matrix theory)  
Fund: Project supported by the Fund from National Board of Higher Mathematics (NBHM), New Delhi (Grant No. 2/48/10/2011-R&D-II/865).
Corresponding Authors:  M. Syed Ali     E-mail:  syedgru@gmail.com
About author:  02.30.Hq; 02.30.Ks; 05.45.-a; 02.10.Yn

Cite this article: 

M. Syed Ali, R. Saravanakumar Augmented Lyapunov approach to H state estimation of static neural networks with discrete and distributed time-varying delays 2015 Chin. Phys. B 24 050201

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