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• W2079281119 endingPage "2761" @default.
• W2079281119 startingPage "2753" @default.
• W2079281119 abstract "In this paper, the problem of distributed consensus estimation with randomly missing measurements is investigated for a diffusion system over the sensor network. A random variable, the probability of which is known a priori, is used to model the randomly missing phenomena for each sensor. The aim of the addressed estimation problem is to design distributed consensus estimators depending on the neighbouring information such that, for all random measurement missing, the estimation error systems are guaranteed to be globally asymptotically stable in the mean square. By using Lyapunov functional method and the stochastic analysis approach, the sufficient conditions are derived for the convergence of the estimation error systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed distributed consensus estimator design scheme." @default.
• W2079281119 created "2016-06-24" @default.
• W2079281119 creator A5013022106 @default.
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• W2079281119 date "2015-03-19" @default.
• W2079281119 modified "2023-10-13" @default.
• W2079281119 title "Distributed consensus estimation for diffusion systems with missing measurements over sensor networks" @default.
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• W2079281119 doi "https://doi.org/10.1080/00207721.2015.1021289" @default.
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