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Type: Journal article
Title: State estimation for discrete-time neural networks with time-varying delay
Author: Wu, Z.
Shi, P.
Su, H.
Chu, J.
Citation: International Journal of Systems Science, 2012; 43(4):647-655
Publisher: Taylor & Francis Ltd
Issue Date: 2012
ISSN: 0020-7721
Statement of
Zhengguang Wu, Peng Shi, Hongye Su and Jian Chu
Abstract: This article deals with the problem of delay-dependent state estimation for discrete-time neural networks with time-varying delay. Our objective is to design a state estimator for the neuron states through available output measurements such that the error state system is guaranteed to be globally exponentially stable. Based on the linear matrix inequality approach, a delay-dependent condition is developed for the existence of the desired state estimator via a novel Lyapunov functional. The obtained condition has less conservativeness than the existing ones, which is demonstrated by a numerical example.
Keywords: neural networks
time-varying delay
state estimation
exponential stability
linear matrix inequality (LMI)
Rights: © 2012 Taylor & Francis
DOI: 10.1080/00207721.2010.517870
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Appears in Collections:Aurora harvest 4
Electrical and Electronic Engineering publications

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