Results 241 to 250 of about 11,537 (265)

Kalman and Particle Filtering

2008
The Kalman and particle filters are algorithms that recursively update an estimate of the state and find the innovations driving a stochastic process given a sequence of observations. The Kalman filter accomplishes this goal by linear projections, while the particle filter does so by a sequential Monte Carlo method.
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Consistency checks for particle filters

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
An "inconsistent" particle filter produces--in a statistical sense--larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior. The statistical properties of the variables are analyzed.
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Particle Filtering

IEEE Signal Processing Magazine, 2003
Petar M. Djuric, Jayesh H. Kotecha, Jianqui Zhang, Yufei Huang 0001, Tadesse Ghirmai, Mónica F. Bugallo, Joaquín Míguez   +6 more
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Nonlinear filtering with particle filters

2014
Convective phenomena in the atmosphere, such as convective storms, are characterized by very fast, intermittent and seemingly stochastic processes. They are thus difficult to predict with Numerical Weather Prediction (NWP) models, and difficult to estimate with data assimilation methods that combine prediction and observations.
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Application of deep learning neural networks for the analysis of fluid-particle dynamics in fibrous filters

Chemical Engineering Journal, 2023
Mohammadreza Shirzadi, Tomonori Fukasawa, Kunihiro Fukui   +2 more
exaly  

Prognostic study of ball screws by ensemble data-driven particle filters

Journal of Manufacturing Systems, 2020
Yafei Deng, Du Shichang
exaly  

Comparison of Particle Filter and Extended Kalman Particle Filter

2017
W pracy zostały zaprezentowane trzy algorytmy estymacji – rozszerzony filtr Kalmana, filtr cząsteczkowy (algorytm Bootstrap) i rozszerzony cząsteczkowy filtr Kalmana. Algorytmy filtru cząsteczkowego i rozszerzonego cząsteczkowego filtru Kalmana zostały porównane dla różnej liczby cząsteczek, a wyniki zestawione z wynikami działania rozszerzonego filtru
Michalski, Jacek, Kozierski, Piotr, Zietkiewicz, Joanna   +2 more
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An overview of differentiable particle filters for data-adaptive sequential Bayesian inference

2023
Yunpeng Li
exaly  

Particle filters for high‐dimensional geoscience applications: A review

Quarterly Journal of the Royal Meteorological Society, 2019
Hans R Künsch, Lars Nerger, Roland Potthast   +2 more
exaly  

Particle Filtering

2015
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