State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

doi:10.1088/1674-1056/21/10/100205

中国物理B ›› 2012, Vol. 21 ›› Issue (10): 100205-100205.doi: 10.1088/1674-1056/21/10/100205

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

S. Lakshmanan^a, Ju H. Park^a, H. Y. Jung^a, P. Balasubramaniam^b

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

收稿日期:2012-02-16 修回日期:2012-04-12 出版日期:2012-09-01 发布日期:2012-09-01
基金资助:
Project supported by the 2010 Yeungnam University Research Grant.

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

S. Lakshmanan^a, Ju H. Park^a, H. Y. Jung^a, P. Balasubramaniam^b

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

Received:2012-02-16 Revised:2012-04-12 Online:2012-09-01 Published:2012-09-01
Contact: Ju H. Park, H. Y. Jung E-mail:jessie@ynu.ac.kr; hoyoul@yu.ac.kr
Supported by:
Project supported by the 2010 Yeungnam University Research Grant.

摘要/Abstract

摘要： 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.

关键词: neural networks, state estimation, neutral delay, Markovian jumping parameters

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.

Key words: neural networks, state estimation, neutral delay, Markovian jumping parameters

中图分类号: (Delay and functional equations)

02.30.Ks

05.45.Gg (Control of chaos, applications of chaos)

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[J]. 中国物理B, 2012, 21(10): 100205-100205.

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State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

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