This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters.
The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.
表中的内容
Nonlinear Data Assimiliatoin for High-Dimensional Systems.- Assimilating Data into Scientific Models: An Optimal Coupling Perspective.关于作者
Peter Jan van Leeuwen is a Professor of Data Assimilation at the University of Reading. His research interests include nonlinear data assimilation, geophysical fluid dynamics, interaction thermohaline and wind-driven ocean circulation, and perturbation theory.Sebastian Reich is a Professor in the Department of Numerical Mathematics at Universität Potsdam. His research interests include uncertainty quantification, geophysical fluid dynamics, molecular dynamics, and geometric integration.
语言 英语 ● 格式 PDF ● 网页 118 ● ISBN 9783319183473 ● 文件大小 2.2 MB ● 出版者 Springer International Publishing ● 市 Cham ● 国家 CH ● 发布时间 2015 ● 下载 24 个月 ● 货币 EUR ● ID 4455903 ● 复制保护 无