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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 |
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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.
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Received: 16 February 2012
Revised: 12 April 2012
Accepted manuscript online:
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PACS:
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02.30.Ks
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(Delay and functional equations)
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05.45.Gg
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(Control of chaos, applications of chaos)
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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
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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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