Localized ensemble Kalman inversion
Sign Up to like & getrecommendations! Published in 2022 at "Inverse Problems"
DOI: 10.1088/1361-6420/accb08
Abstract: Ensemble Kalman inversion (EKI) is an adaption of the ensemble Kalman filter (EnKF) for the numerical solution of inverse problems. Both EKI and EnKF suffer from the ‘subspace property’, i.e. the EKI and EnKF solutions… read more here.
Keywords: kalman inversion; ensemble kalman; inverse problems; ensemble size ... See more keywords
Less Is More: A Comprehensive Framework for the Number of Components of Ensemble Classifiers
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2018.2886341
Abstract: The number of component classifiers chosen for an ensemble greatly impacts the prediction ability. In this paper, we use a geometric framework for a priori determining the ensemble size, which is applicable to most of… read more here.
Keywords: number; ensemble size; less comprehensive; number components ... See more keywords
On the selection of localization radius in ensemble filtering for multiscale quasigeostrophic dynamics
Sign Up to like & getrecommendations! Published in 2018 at "Monthly Weather Review"
DOI: 10.1175/mwr-d-17-0336.1
Abstract: AbstractCovariance localization remedies sampling errors due to limited ensemble size in ensemble data assimilation. Previous studies suggest that the optimal localization radius depends on ensemble size, observation density and accuracy, as well as the correlation… read more here.
Keywords: ensemble size; radius ensemble; localization radius; localization ... See more keywords