Results 11 to 20 of about 65,516 (291)
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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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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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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Physica D: Nonlinear Phenomena, 2001 41 pages, 9 figures, correction of errors in the general multivariate ...
Sornette, Didier, Ide, Kayo
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Comparative study of state and unknown input estimation for continuous–discrete stochastic systems
Franklin Open, 2022 Joint state and unknown input estimation for continuous–discrete stochastic systems can be classified into two types: with and without modeling of unknown inputs.
Peng Lu
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Joint semi-blind detection and channel estimation in space-frequency trellis coded MIMO-OFDM [PDF]
, 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
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Journal 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.
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A New Fusion Estimation Method for Multi-Rate Multi-Sensor Systems With Missing Measurements
IEEE Access, 2020 A new fusion strategy is introduced in this article to estimate state for multi-rate multi-sensor systems with missing measurements. N sensors, which possess various sampling rates, render the measurements. Missing measurements with a certain probability
Mojtaba Kordestani +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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Journal 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.
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