State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters |
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Authors: | S Lakshmanan Ju H Park H Y Jung P Balasubramaniam |
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Institution: | 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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Keywords: | neural networks state estimation neutral delay Markovian jumping parameters |
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