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Nonlinear filtering for a Chemostat model

Abstract : We aim in this paper to estimate the state variables of a stochastic Chemostat model using three methods, the extended Kalman filter, the unscented Kalman filter and the particle filter(bootstrap). The results obtained from these three algorithms are compared to choose which one of them is the best method for state estimation for this type of systems.
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Preprints, Working Papers, ...
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https://hal.inria.fr/hal-01316362
Contributor : Oussama Hadj Abdelkader <>
Submitted on : Monday, May 16, 2016 - 6:53:10 PM
Last modification on : Wednesday, September 7, 2016 - 1:01:04 AM
Long-term archiving on: : Wednesday, November 16, 2016 - 6:00:17 AM

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Oussama Hadj Abdelkader, Mohamed Amine Hadj Abdelkader. Nonlinear filtering for a Chemostat model. 2016. ⟨hal-01316362⟩

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