73 citations as recorded by crossref.

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15. Assimilation of low-level wind in a high-resolution mesoscale model using the back and forth nudging algorithm A. Boilley & J. Mahfouf 10.3402/tellusa.v64i0.18697
16. Back-and-forth nudging moving horizon estimation for discrete-time linear systems J. Xie & B. Huang 10.1016/j.automatica.2024.111691
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20. A new back‐and‐forth iterative method for time‐reversed convection modeling: Implications for the Cenozoic evolution of 3‐D structure and dynamics of the mantle P. Glišović & A. Forte 10.1002/2016JB012841
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24. Joint Estimation of Balanced Motions and Internal Tides From Future Wide‐Swath Altimetry F. Le Guillou et al. 10.1029/2021MS002613
25. Enhanced retrospective forecasting in dissipative dynamical systems using transformer and multi-scale ESRGAN models M. Zhang et al. 10.1016/j.rineng.2024.103597
26. Effect of discrete time observations on synchronization in Chua model and applications to data assimilation M. Nurujjaman et al. 10.1063/1.4712591
27. Derivative‐free optimization for large‐scale nonlinear data assimilation problems S. Gratton et al. 10.1002/qj.2169
28. Improving Numerical Dispersion Modelling in Built Environments with Data Assimilation Using the Iterative Ensemble Kalman Smoother C. Defforge et al. 10.1007/s10546-020-00588-9
29. Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model G. Ruggiero et al. 10.5194/npg-22-233-2015
30. Iterative observer-based state and parameter estimation for linear systems A. Aalto 10.1051/cocv/2017005
31. Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows S. Pawar et al. 10.1063/5.0012853
32. Sequential identification of boundary support parameters in a fluid-structure vascular model using patient image data P. Moireau et al. 10.1007/s10237-012-0418-3
33. Downscaling data assimilation algorithm with applications to statistical solutions of the Navier–Stokes equations C. Mondaini et al. 10.1016/j.anihpc.2018.05.004
34. Data Assimilation in Large Prandtl Rayleigh--Bénard Convection from Thermal Measurements A. Farhat et al. 10.1137/19M1248327
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36. Continuous data assimilation for two-phase flow: Analysis and simulations Y. Chow et al. 10.1016/j.jcp.2022.111395
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41. A Spatially Dependent Nudging Method and Its Application to a Global Tide Assimilation L. Liu & X. Chen 10.1007/s00376-024-4062-5
42. Mapping Altimetry in the Forthcoming SWOT Era by Back-and-Forth Nudging a One-Layer Quasigeostrophic Model F. Le Guillou et al. 10.1175/JTECH-D-20-0104.1
43. Data Assimilation for the Navier--Stokes Equations Using Local Observables A. Biswas et al. 10.1137/20M136058X
44. Reconstructing the initial state for the nonlinear system and analyzing its convergence W. Xie & Y. Chang 10.1186/1687-1847-2014-82
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46. Full-field and anomaly initialization using a low-order climate model: a comparison and proposals for advanced formulations A. Carrassi et al. 10.5194/npg-21-521-2014
47. Reconstructing the Initial State of the Linear System and Estimating its Error in Discretization R. Wang & W. Xie 10.11650/tjm/221105
48. An easy-to-implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging (BFN) algorithm D. Auroux et al. 10.1088/1742-6596/135/1/012011
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50. State reconstruction of a distributed parameter system with exact observability G. Xu 10.1016/j.jmaa.2013.06.014
51. An evolution of the back and forth nudging for geophysical data assimilation: application to Burgers equation and comparisons D. Auroux et al. 10.1080/17415977.2012.712528
52. Finite time synchronization of the continuous/discrete data assimilation algorithms for Lorenz 63 system based on the back and forth nudging techniques Y. Peng et al. 10.1016/j.rinam.2023.100407
53. Ocean‐depth measurement using shallow‐water wave models V. Vasan et al. 10.1111/sapm.12418
54. Fundamental principles of data assimilation underlying the Verdandi library: applications to biophysical model personalization within euHeart D. Chapelle et al. 10.1007/s11517-012-0969-6
55. First results of operational ionospheric dynamics prediction for the Brazilian Space Weather program A. Petry et al. 10.1016/j.asr.2014.03.017
56. Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method W. Mao et al. 10.1155/2020/5491957
57. On the physical nudging equations G. Conti et al. 10.1007/s00382-021-05972-w
58. Dynamic Initialization for Whole Atmospheric Global Modeling I. Song et al. 10.1029/2017MS001213
59. Data assimilation in the geosciences: An overview of methods, issues, and perspectives A. Carrassi et al. 10.1002/wcc.535
60. Continuous Data Assimilation for the Three-Dimensional Navier--Stokes Equations A. Biswas & R. Price 10.1137/20M1323229
61. A time reversal based algorithm for solving initial data inverse problems K. Ito et al. 10.3934/dcdss.2011.4.641
62. Continuous data assimilation for the 3D Ladyzhenskaya model: analysis and computations Y. Cao et al. 10.1016/j.nonrwa.2022.103659
63. Data assimilation in 2D hyperbolic/parabolic systems using a stabilized explicit finite difference scheme run backward in time A. Carasso 10.1080/27690911.2023.2282641
64. Methods for Observation Data Assimilation in Problems of Physics of Atmosphere and Ocean V. Shutyaev 10.1134/S0001433819010080
65. Output error minimizing back and forth nudging method for initial state recovery A. Aalto 10.1016/j.sysconle.2016.06.002
66. Sources of skill in near-term climate prediction: generating initial conditions A. Carrassi et al. 10.1007/s00382-016-3036-4
67. Object-Based Analog Forecasts for Surface Wind Speed M. Frediani et al. 10.1175/MWR-D-17-0012.1
68. An efficient data assimilation algorithm using the Allen–Cahn equation B. Xia et al. 10.1016/j.enganabound.2023.06.029
69. Data assimilation with regularized nonlinear instabilities H. Abarbanel et al. 10.1002/qj.600
70. A Switching Observer for a Class of Nonuniformly Observable Systems via Singular Time-Rescaling M. Aguado-Rojas et al. 10.1109/TAC.2021.3062340
71. Model and observation‐error covariance matrix information in the physical nudging equations G. Conti et al. 10.1002/qj.4979
72. Luenberger Observers for Infinite-Dimensional Systems, Back and Forth Nudging, and Application to a Crystallization Process L. Brivadis et al. 10.1137/20M1329020
73. Symmetry-Based Observers for Some Water-Tank Problems D. Auroux & S. Bonnabel 10.1109/TAC.2010.2067291