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

journal contribution
posted on 2023-10-26, 03:21 authored by Lakshmanan Shanmugam, J H Park, H Y Jung, P Balasubramaniam
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. © 2012 Chinese Physical Society and IOP Publishing Ltd.

History

Journal

Chinese physics b

Volume

21

Article number

100205

Location

Bristol, Eng.

ISSN

1674-1056

Language

eng

Copyright notice

2012, Chinese Physical Society and IOP Publishing Ltd

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