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Particle filter applied to polynomial chaotic maps

Moussa Yahia 1 Pascal Acco 1
1 LAAS-S4M - Équipe Instrumentation embarquée et systèmes de surveillance intelligents
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.
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Contributor : Pascal Acco <>
Submitted on : Friday, September 20, 2019 - 10:51:11 AM
Last modification on : Thursday, June 10, 2021 - 3:03:57 AM



Moussa Yahia, Pascal Acco. Particle filter applied to polynomial chaotic maps. 2009 European Conference on Circuit Theory and Design (ECCTD 2009), Aug 2009, Antalya, France. ⟨10.1109/ECCTD.2009.5275041⟩. ⟨hal-01886022⟩



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