Results 41 to 50 of about 11,537 (265)
Weighted ensemble transform Kalman filter for image assimilation [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2013 This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF) proposed by Papadakis et al. (2010) for the assimilation of image observations.
Sebastien Beyou +3 more
doaj +1 more source
Saturated particle filter [PDF]
Proceedings of the 2011 American Control Conference, 2011 In many practical applications the state variables are defined on a compact set of the state space. For estimating such variables constrained particle filters have been successfully applied to nonlinear systems. For the saturated system the measurement information can be used during the sampling procedure to obtain particles that approximate the true ...
Pawel Stano +2 more
openaire +1 more source
Parallelized Particle and Gaussian Sum Particle Filters for Large Scale Freeway Traffic Systems [PDF]
, 2012 Large scale traffic systems require techniques able to: 1) deal with high amounts of data and heterogenous data coming from different types of sensors, 2) provide robustness in the presence of sparse sensor data, 3) incorporate different models that can ...
Gning, Amadou +7 more
core +1 more source
Particle Learning Methods for State and Parameter Estimation [PDF]
, 2012 This paper presents an approach for online parameter estimation within particle lters. Current research has mainly been focused towards the estimation of static parameters.
Fearnhead, Paul +7 more
core +1 more source
Particle Flow Gaussian Particle Filter
2022 25th International Conference on Information Fusion (FUSION), 2022 State estimation in non-linear models is performed by tracking the posterior distribution recursively. A plethora of algorithms have been proposed for this task. Among them, the Gaussian particle filter uses a weighted set of particles to construct a Gaussian approximation to the posterior.
Comandur, Karthik +2 more
openaire +4 more sources
Resampling Algorithms for Particle Filters: A Computational Complexity Perspective
EURASIP Journal on Advances in Signal Processing, 2004 Newly developed resampling algorithms for particle filters suitable for real-time implementation are described and their analysis is presented. The new algorithms reduce the complexity of both hardware and DSP realization through addressing common issues
Miodrag Bolić +2 more
doaj +1 more source
MapReduce particle filtering with exact resampling and deterministic runtime
EURASIP Journal on Advances in Signal Processing, 2017 Particle filtering is a numerical Bayesian technique that has great potential for solving sequential estimation problems involving non-linear and non-Gaussian models.
Jeyarajan Thiyagalingam +2 more
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CFD-DEM Study of Pleated Filter Plugging Process Based on Porous Media Model
Machines, 2022 The pneumatic conveying process of fine particles through filters was studied by CFD-DEM simulation method. The porous media model and porous structure were used to simulate the airflow state and the blocking effect of fine particles when they flowed ...
Yinhang Zhang +4 more
doaj +1 more source
A particle filter for freeway traffic estimation [PDF]
, 2004 This paper considers the traffic flow estimation problem for the purposes of on-line traffic prediction, mode detection and ramp-metering control. The solution to the estimation problem is given within the Bayesian recursive framework. A particle filter (
Mihaylova, Lyudmila +7 more
core +1 more source
Indoor EnvironmentsElectrospun nanofiber air filters can achieve high particle filtration efficiency with lower pressure drop compared with high-efficiency particulate air (HEPA) filters. Therefore, they can potentially be used for effective indoor particle removal.
Zhuolun Niu, Chun Chen
doaj +1 more source