Results 1 to 10 of about 64,413 (127)

Multiplicative Kalman filtering [PDF]

open access: yesTEST, 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
openaire   +3 more sources

Autodifferentiable Ensemble Kalman Filters

open access: yesSIAM 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
openaire   +3 more sources

Multimodal Kalman filtering [PDF]

open access: yes2016 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
openaire   +2 more sources

Differentially private Kalman filtering [PDF]

open access: yes2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012
9 pages.
Ny, Jerome Le, Pappas, George J.
openaire   +2 more sources

The Kalman–Lévy filter [PDF]

open access: yesPhysica D: Nonlinear Phenomena, 2001
41 pages, 9 figures, correction of errors in the general multivariate ...
Sornette, Didier, Ide, Kayo
openaire   +3 more sources

Adaptive Kalman Filtering

open access: yesJournal of Research of the National Bureau of Standards, 1985
The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Brown, Steven D., Rutan, Sarah C.
openaire   +3 more sources

Joint semi-blind detection and channel estimation in space-frequency trellis coded MIMO-OFDM [PDF]

open access: yes, 2003
This paper considers an OFDM system with a multiple-input multiple-output (MIMO) configuration, which uses space-frequency trellis coding (SFTC). A novel method of decoding SFTC without a need to transmit separate training sequences is developed.
McGeehan, JP, Nix, AR, Piechocki, RJ
core   +2 more sources

A Unification of Ensemble Square Root Kalman Filters [PDF]

open access: yes, 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
core   +1 more source

Mixture Kalman Filters

open access: yesJournal of the Royal Statistical Society Series B: Statistical Methodology, 2000
Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which
Chen, Rong, Liu, Jun S.
openaire   +2 more sources

Controlling balance in an ensemble Kalman filter [PDF]

open access: yes, 2014
We present a method to control unbalanced fast dynamics in an ensemble Kalman filter by introducing a weak constraint on the imbalance in a spatially sparse observational network.
G. A. Gottwald
core   +1 more source

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