Results 11 to 20 of about 186,344 (275)
Physica D: Nonlinear Phenomena, 2001 41 pages, 9 figures, correction of errors in the general multivariate ...
Sornette, Didier, Ide, Kayo
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Comparisons on Kalman-Filter-Based Dynamic State Estimation Algorithms of Power Systems
IEEE Access, 2020 The Kalman-filter-based algorithms as the mainstream algorithms of dynamic state estimation of power systems have been extensively used to provide accurate data for power system applications. However, few comparisons are made to show their advantages and
Hui Liu +4 more
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AN APPROACH ON ADVANCED UNSCENTED KALMAN FILTER FROM MOBILE ROBOT-SLAM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 In the past 30 years, Kalman filter is a classical method to solve the problem of simultaneous localization and mapping (SLAM) of mobile robots. Extended Kalman filter (EKF) and unscented Kalman filter (UKF) are derived from Kalman filter.
L. Yan, L. Zhao
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MIMU/BDS Integrated Navigation Technology Based on Smooth Variable Structure-Adaptive Kalman Filter [PDF]
Hangkong bingqi, 2021 In order to improve the accuracy of MIMU/BDS integrated navigation with uncertain models and large disturbances, a smoothing variable structure-Kalman combined filter information fusion method is proposed.
Li Can, Shen Qiang, Qin Weiwei, Duan Zhiqiang, Wang Lixin
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InPrime, 2022 This research explains a comparison estimation for AUV position using Kalman Filter (KF), Ensemble Kalman Filter (EnKF), and Fuzzy Kalman Filter (FKF) algorithm in some specified trajectories.
Ngatini Ngatini +2 more
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Kalman Filter and Its Application in Data Assimilation
Atmosphere, 2023 In 1960, R.E. Kalman published his famous paper describing a recursive solution, the Kalman filter, to the discrete-data linear filtering problem.
Bowen Wang +4 more
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TWO-STAGE CUBATURE KALMAN FILTERAND ITS APPLICATION IN WATER POLLUTION MODEL [PDF]
Acta Scientifica Malaysia, 2018 Water Pollution Model is a nonlinear system which present the random bias. The most common method is to use augmented state Cubature Kalman Filter, but the computational requirement of augmented state Kalman filter may become excessive.
Zhang, Xu, Wang
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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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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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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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