Results 1 to 10 of about 94,506 (183)
Advancements in Buoy Wave Data Processing through the Application of the Sage–Husa Adaptive Kalman Filtering Algorithm [PDF]
Sensors, 2023 In this paper, we propose a combined filtering method rooted in the application of the Sage–Husa Adaptive Kalman filtering, designed specifically to process wave sensor data.
Sha Jiang, Yonghua Chen, Qingkui Liu
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Kalman filtering to reduce measurement noise of sample entropy: An electroencephalographic study. [PDF]
PLoS ONEIn the analysis of electroencephalography (EEG), entropy can be used to quantify the rate of generation of new information. Entropy has long been known to suffer from variance that arises from its calculation.
Nan Zhang +6 more
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The Optimal Distributed Kalman Filtering Fusion With Linear Equality Constraint
IEEE Access, 2021 In this paper, the optimal distributed Kalman filtering fusion with linear equality constraint (LEC) is proposed. When the Kalman filter subject to LEC is applied in state estimation of distributed linear dynamic system, all local error covariance ...
Hua Li, Shengli Zhao
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Two-Stage Cubature Kalman Filtering Based on T-Transform and Its Application
Complexity, 2021 According to the actual application system model which has bias, this paper analyzes the shortage of the conventional augmented algorithm, the two-stage cubature Kalman filtering algorithm, which is presented on the basis of a two-stage nonlinear ...
Lu Zhang +3 more
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Inverse problem of incomplete boundaries and unknown parameters in two-dimensional Poisson equation
Nantong Daxue xuebao. Ziran kexue ban, 2022 The inverse problem of Poisson equation with incomplete boundary or unknown parameters have been solved by using the method of fundamental solutions (MFS) and Kalman filtering technique.
WANG Yue; JIANG Quan
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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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Autodifferentiable Ensemble Kalman Filters
SIAM Journal on Mathematics of Data Science, 2022 Data assimilation is concerned with sequentially estimating a temporally-evolving state. This task, which arises in a wide range of scientific and engineering applications, is particularly challenging when the state is high-dimensional and the state-space dynamics are unknown.
Yuming Chen +2 more
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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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Differentially private Kalman filtering [PDF]
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012 9 pages.
Ny, Jerome Le, Pappas, George J.
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Double hybrid Kalman filtering for state estimation of dynamical systems [PDF]
ITM Web of Conferences, 2019 In this paper authors present a new approaches to the hybrid Kalman filtering and modified hybrid Kalman filtering, with the changed order of methods inside (Unscented Kalman Filter and Extended Kalman Filter).
Michalski Jacek +2 more
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