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Chin. Phys. B, 2012, Vol. 21(10): 100205    DOI: 10.1088/1674-1056/21/10/100205
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State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

S. Lakshmanana, Ju H. Parka, H. Y. Junga, P. Balasubramaniamb
a Department of Information and Communication Engineering/Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan 712-749, Republic of Korea;
b Department of Mathematics, Gandhigram Rural Institute-Deemed University, Gandhigram-624 302, Tamilnadu, India
Abstract  This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed time-varying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov-Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages.
Keywords:  neural networks      state estimation      neutral delay      Markovian jumping parameters  
Received:  16 February 2012      Revised:  12 April 2012      Accepted manuscript online: 
PACS:  02.30.Ks (Delay and functional equations)  
  05.45.Gg (Control of chaos, applications of chaos)  
Fund: Project supported by the 2010 Yeungnam University Research Grant.
Corresponding Authors:  Ju H. Park, H. Y. Jung     E-mail:  jessie@ynu.ac.kr; hoyoul@yu.ac.kr

Cite this article: 

S. Lakshmanan, Ju H. Park, H. Y. Jung, P. Balasubramaniam State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters 2012 Chin. Phys. B 21 100205

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