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Nonlinear data assimilation

Leeuwen, Peter Jan van.

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Nonlinear data assimilation

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonlinear data assimilation/ by Peter Jan Van Leeuwen, Yuan Cheng, Sebastian Reich.
Author:	Leeuwen, Peter Jan van.
other author:	Cheng, Yuan.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xii, 116 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Simulation methods. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-18347-3
ISBN:	9783319183473 (electronic bk.)

Nonlinear data assimilation
Leeuwen, Peter Jan van.

Nonlinear data assimilation[electronic resource] /by Peter Jan Van Leeuwen, Yuan Cheng, Sebastian Reich. - Cham :Springer International Publishing :2015. - xii, 116 p. :ill., digital ;24 cm. - Frontiers in applied dynamical systems: reviews and tutorials,v.22364-4532 ;. - Frontiers in applied dynamical systems.Reviews and tutorials ;v.2..

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.

ISBN: 9783319183473 (electronic bk.)

Standard No.: 10.1007/978-3-319-18347-3doiSubjects--Topical Terms:

581321
Simulation methods.

LC Class. No.: QA401

Dewey Class. No.: 511.8

Nonlinear data assimilation
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245 1 0 $a Nonlinear data assimilation $h [electronic resource] / $c by Peter Jan Van Leeuwen, Yuan Cheng, Sebastian Reich.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xii, 116 p. : $b ill., digital ; $c 24 cm.
490 1 $a Frontiers in applied dynamical systems: reviews and tutorials, $x 2364-4532 ; $v v.2
520 $a 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.
650 0 $a Simulation methods. $3 581321
650 0 $a Mathematical models. $3 522882
650 1 4 $a Mathematics. $3 515831
650 2 4 $a Dynamical Systems and Ergodic Theory. $3 891276
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 891040
650 2 4 $a Mathematical Applications in the Physical Sciences. $3 1566152
700 1 $a Cheng, Yuan. $3 1916120
700 1 $a Reich, Sebastian. $3 865036
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830 0 $a Frontiers in applied dynamical systems. $p Reviews and tutorials ; $v v.2. $3 2157944
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950 $a Mathematics and Statistics (Springer-11649)