Results 11 to 20 of about 1,778,758 (298)
IEEE Access, 2021 We present an approach which combines the sample regenerating particle filter (SRGPF) and unequal weight ensemble Kalman filter (UwEnKF) to obtain a more accurate forecast for nonlinear dynamic systems.
Xiao Li, Ai Jie Cheng, Hai Xiang Lin
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Kalman Filter: Historical Overview and Review of Its Use in Robotics 60 Years after Its Creation
J. Sensors, 2021 Due to its widespread application in the robotics field, the Kalman filter has received increased attention from researchers. This work reviews some of the modifications conducted on to this algorithm over the last years. Problems such as the consistency,
C. Urrea, Rayko Agramonte
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Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter
Mathematics, 2022 Time series forecasting is one of the main venues followed by researchers in all areas. For this reason, we develop a new Kalman filter approach, which we call the alternative Kalman filter. The search conditions associated with the standard deviation of
Juan D. Borrero, Jesus Mariscal
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Student’s t-Kernel-Based Maximum Correntropy Kalman Filter
Sensors, 2022 The state estimation problem is ubiquitous in many fields, and the common state estimation method is the Kalman filter. However, the Kalman filter is based on the mean square error criterion, which can only capture the second-order statistics of the ...
Hongliang Huang, Hai Zhang
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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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SN Applied Sciences, 2022 In this paper, a risk sensitive estimator based on cubature quadrature Kalman filter is formulated and applied for tracking a ballistic object during its re-entry phase.
Swati
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Machines, 2023 This paper analyzes the performance of Kalman filter-based estimators for robust filtering and rotor asymmetry detection in wound rotor induction machines (WRIMs) using real-time data. Filter models were designed based on an extended model of WRIMs.
Furzana John Basha, Kumar Somasundaram
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The Endogenous Kalman Filter [PDF]
SSRN Electronic Journal, 2007 We relax the assumption of full information that underlies most dynamic general equilibrium models, and instead assume agents optimally form estimates of the states from an incomplete information set. We derive a version of the Kalman filter that is endogenous to agents' optimising decisions, and state conditions for its convergence.
Brad Baxter, Liam Graham, Stephen Wright
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Multimodal Kalman filtering [PDF]
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 A difficult aspect of multimodal estimation is the possible discrepancy between the sampling rates and/or the noise levels of the considered data. Many algorithms cope with these dissimilarities empirically. In this paper, we propose a conceptual analysis of multimodality where we try to find the "optimal" way of combining modalities. More specifically,
Bourrier, Anthony +3 more
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A Unification of Ensemble Square Root Kalman Filters [PDF]
, 2012 In recent years, several ensemble-based Kalman filter algorithms have been developed that have been classified as ensemble square-root Kalman filters.
Hiller, Wolfgang +3 more
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