Nonlinear data assimilation /

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...

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Bibliographic Details
Main Author: Van Leeuwen, Peter Jan (Author)
Corporate Author: SpringerLink (Online service)
Other Authors: Cheng, Yuan, Reich, Sebastian
Format: eBook
Language:English
Published: Cham Springer International Publishing 2015.
Edition:1st ed. 2015.
Series:Frontiers in Applied Dynamical Systems: Reviews and Tutorials 2
Subjects:
Online Access:Click here to view the full text content
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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. 
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