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Le filtrage linéaire et non linéaire à temps discret et à temps continu et applications

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dc.contributor.author El-Hadj Ali, Thouria
dc.contributor.author Bousseboua, M.
dc.date.accessioned 2022-05-25T08:50:53Z
dc.date.available 2022-05-25T08:50:53Z
dc.date.issued 2012-06-14
dc.identifier.uri http://depot.umc.edu.dz/handle/123456789/9207
dc.description.abstract The object of this work concerns on the estimate of the state of linear and nonlinear dynamic system and some applications of the problem of filtering in various fields. After a concise talk of the basic concepts of stochastic calculation, various approaches to the problem of filtering have been considered according to temporal nature and the linear or not linear aspect of the system. In the case of a linear dynamic system, we use the approach innovation to find the optimal kalman filter and in particular we find the kalman-Bucy filter in the case of the Gaussian systems. When the dynamic system is nonlinear, the discrete time filter is deduced from the Kalman filter after linearizing of the system and in the case of continuous time, the optimal filter is obtained according to the approach change of measurement initially and then the approach innovation. Three applications to illustrate the interest and the effectiveness of filtering theory were initiated in signal processing, navigation and finance.
dc.language.iso fr
dc.publisher Université Frères Mentouri - Constantine 1
dc.subject Système dynamique stochastique
dc.subject le filtre de Kalman
dc.subject équation de Zakai
dc.subject équation de Kushner
dc.subject Stochastic dynamic system
dc.subject the Kalman filter
dc.subject Zakai equation
dc.subject Kushner equation
dc.title Le filtrage linéaire et non linéaire à temps discret et à temps continu et applications
dc.type Thesis

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