A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI
A Discontinuous Extended Kalman Filter for Non-Smooth Dynamic Problems M.N. Chatzis a, E.N. Chatzi b and S.P. Triantafyllou a
![Frontiers | Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching | Applied Mathematics and Statistics Frontiers | Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching | Applied Mathematics and Statistics](https://www.frontiersin.org/files/Articles/482379/fams-05-00047-HTML/image_m/fams-05-00047-g001.jpg)
Frontiers | Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching | Applied Mathematics and Statistics
![State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter - ScienceDirect State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter - ScienceDirect](https://ars.els-cdn.com/content/image/1-s2.0-S0306261918305531-gr2.jpg)
State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter - ScienceDirect
Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation
![HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology](https://hess.copernicus.org/articles/23/1163/2019/hess-23-1163-2019-f01-web.png)
HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology
Background Error Covariance Iterative Updating with Invariant Observation Measures for Data Assimilation
![Error covariance tuning in variational data assimilation: application to an operating hydrological model | SpringerLink Error covariance tuning in variational data assimilation: application to an operating hydrological model | SpringerLink](https://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00477-020-01933-7/MediaObjects/477_2020_1933_Fig5_HTML.png)
Error covariance tuning in variational data assimilation: application to an operating hydrological model | SpringerLink
![HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology](https://hess.copernicus.org/articles/23/1163/2019/hess-23-1163-2019-f02-web.png)
HESS - Covariance resampling for particle filter – state and parameter estimation for soil hydrology
A State Optimization Model Based on Kalman Filtering and Robust Estimation Theory for Fusion of Multi-Source Information in High
![Mathematics | Free Full-Text | Automatic Calibration of Process Noise Matrix and Measurement Noise Covariance for Multi-GNSS Precise Point Positioning | HTML Mathematics | Free Full-Text | Automatic Calibration of Process Noise Matrix and Measurement Noise Covariance for Multi-GNSS Precise Point Positioning | HTML](https://www.mdpi.com/mathematics/mathematics-08-00502/article_deploy/html/images/mathematics-08-00502-g008.png)