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

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

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

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