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＜E-Book＞
Nonlinear Data Assimilation / by Peter Jan Van Leeuwen, Yuan Cheng, Sebastian Reich
(Frontiers in Applied Dynamical Systems: Reviews and Tutorials. ISSN:23644931 ; 2)

Edition	1st ed. 2015.
Publisher	(Cham : Springer International Publishing : Imprint: Springer)
Year	2015
Size	XII, 118 p. 19 illus., 15 illus. in color : online resource
Authors	*Van Leeuwen, Peter Jan author Cheng, Yuan author Reich, Sebastian author SpringerLink (Online service)
Subjects	LCSH:Dynamical systems LCSH:Mathematics—Data processing LCSH:Mathematical physics FREE:Dynamical Systems FREE:Computational Mathematics and Numerical Analysis FREE:Mathematical Physics
Notes	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 HTTP:URL=https://doi.org/10.1007/978-3-319-18347-3

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