Παρακολούθηση
Boujemaa AIT EL FQUIH
Boujemaa AIT EL FQUIH
Research Scientist, KAUST
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα kaust.edu.sa
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Estimating model‐error covariances in nonlinear state‐space models using Kalman smoothing and the expectation–maximization algorithm
D Dreano, P Tandeo, M Pulido, B Ait‐El‐Fquih, T Chonavel, I Hoteit
Quarterly Journal of the Royal Meteorological Society 143 (705), 1877-1885, 2017
692017
An iterative ensemble Kalman filter with one-step-ahead smoothing for state-parameters estimation of contaminant transport models
ME Gharamti, B Ait-El-Fquih, I Hoteit
Journal of Hydrology 527, 442-457, 2015
622015
Kalman filtering in triplet Markov chains
B Ait-El-Fquih, F Desbouvries
IEEE Transactions on Signal Processing 54 (8), 2957-2963, 2006
602006
A two-update ensemble Kalman filter for land hydrological data assimilation with an uncertain constraint
M Khaki, B Ait-El-Fquih, I Hoteit, E Forootan, J Awange, M Kuhn
Journal of Hydrology 555, 447-462, 2017
552017
Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the red sea
I Hoteit, Y Abualnaja, S Afzal, B Ait-El-Fquih, T Akylas, C Antony, ...
Bulletin of the American Meteorological Society 102 (1), E99-E122, 2021
542021
Data assimilation in oceanography: Current status and new directions
I Hoteit, X Luo, M Bocquet, A Kohl, B Ait-El-Fquih
New frontiers in operational oceanography, 465-512, 2018
482018
Enhanced flood forecasting through ensemble data assimilation and joint state-parameter estimation
MG Ziliani, R Ghostine, B Ait-El-Fquih, MF McCabe, I Hoteit
Journal of Hydrology 577, 123924, 2019
462019
A variational Bayesian multiple particle filtering scheme for large-dimensional systems
B Ait-El-Fquih, I Hoteit
IEEE Transactions on Signal Processing 64 (20), 5409-5422, 2016
442016
Efficient kernel-based ensemble Gaussian mixture filtering
B Liu, B Ait-El-Fquih, I Hoteit
Monthly Weather Review 144 (2), 781-800, 2016
422016
A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology
B Ait-El-Fquih, M El Gharamti, I Hoteit
Hydrology and Earth System Sciences 20 (8), 3289-3307, 2016
412016
Fast Kalman-like filtering for large-dimensional linear and Gaussian state-space models
B Ait-El-Fquih, I Hoteit
IEEE Transactions on Signal Processing 63 (21), 5853-5867, 2015
382015
Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation
M Khaki, B Ait-El-Fquih, I Hoteit, E Forootan, J Awange, M Kuhn
Journal of Hydrology 564, 175-190, 2018
342018
Direct, prediction-and smoothing-based Kalman and particle filter algorithms
F Desbouvries, Y Petetin, B Ait-El-Fquih
Signal processing 91 (8), 2064-2077, 2011
342011
On Bayesian fixed-interval smoothing algorithms
B Ait-El-Fquih, F Desbouvries
IEEE Transactions on Automatic Control 53 (10), 2437-2442, 2008
312008
A fixed-lag particle smoother for blind SISO equalization of time-varying channels
A Guimarães, B Ait-El-Fquih, F Desbouvries
IEEE transactions on wireless communications 9 (2), 512-516, 2010
232010
Calibrating land hydrological models and enhancing their forecasting skills using an ensemble Kalman filter with one-step-ahead smoothing
M Khaki, B Ait-El-Fquih, I Hoteit
Journal of Hydrology 584, 124708, 2020
202020
A reduced-order variational Bayesian approach for efficient subsurface imaging
D Urozayev, B Ait-El-Fquih, I Hoteit, D Peter
Geophysical Journal International 229 (2), 838-852, 2022
192022
Parametric Bayesian estimation of point-like pollution sources of groundwater layers
B Ait-El-Fquih, JF Giovannelli, N Paul, A Girard, I Hoteit
Signal Processing 168, 107339, 2020
172020
Ensemble Kalman filtering with one-step-ahead smoothing
NF Raboudi, B Ait-El-Fquih, I Hoteit
Monthly Weather Review 146 (2), 561-581, 2018
162018
Unsupervised signal restoration in partially observed Markov chains
BA El Fquih, F Desbouvries
2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006
162006
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