Nonlinear Data Assimilation / by Peter Jan Van Leeuwen, Yuan Cheng, Sebastian Reich

By:

Van Leeuwen, Peter Jan [aut]

Contributor(s):

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Frontiers in Applied Dynamical Systems: Reviews and Tutorials ; 2 | SpringerLink BücherPublisher: Cham ; s.l. : Springer International Publishing, 2015Edition: 1st ed. 2015Description: Online-Ressource (XII, 118 p. 19 illus., 15 illus. in color, online resource)ISBN:

9783319183473

Subject(s):

Additional physical formats: 9783319183466 | Druckausg.: Nonlinear data assimilation. Cham : Springer, 2015. xii, 118 SeitenMSC: MSC: *62-02 | 62-07 | 62M20 | 62G05 | 65C05 | 62F15 | 86A32 | 93E11LOC classification:

QA313

DOI: DOI: 10.1007/978-3-319-18347-3Online resources:

Contents:

Summary: 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 nowPPN: PPN: 1657534413Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SXMS | ZDB-2-SMA

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