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Nonlinear data assimilation / Peter Jan van Leeuwen, Yuan Cheng, Sebastian Reich
| Nonlinear data assimilation / Peter Jan van Leeuwen, Yuan Cheng, Sebastian Reich |
| Autore | Leeuwen, Peter Jan : van |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XII, 118 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cheng, Yuan
Reich, Sebastian |
| Soggetto topico |
65C05 - Monte Carlo methods [MSC 2020]
35R30 - Inverse problems for PDEs [MSC 2020] 86A22 - Inverse problems in geophysics [MSC 2020] 93E11 - Filtering in stochastic control theory [MSC 2020] 62F15 - Bayesian inference [MSC 2020] 62M20 - Inference from stochastic processes and prediction; filtering [MSC 2020] |
| Soggetto non controllato |
Applied dynamical systems
Data Assimilation Nonlinear data Particle filters Proposal densities |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113544 |
Leeuwen, Peter Jan : van
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| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Nonlinear data assimilation / Peter Jan van Leeuwen, Yuan Cheng, Sebastian Reich
| Nonlinear data assimilation / Peter Jan van Leeuwen, Yuan Cheng, Sebastian Reich |
| Autore | Leeuwen, Peter J. van |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | XII, 118 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Cheng, Yuan
Reich, Sebastian |
| Soggetto topico |
35R30 - Inverse problems for PDEs [MSC 2020]
62F15 - Bayesian inference [MSC 2020] 62M20 - Inference from stochastic processes and prediction; filtering [MSC 2020] 65C05 - Monte Carlo methods [MSC 2020] 86A22 - Inverse problems in geophysics [MSC 2020] 93E11 - Filtering in stochastic control theory [MSC 2020] |
| Soggetto non controllato |
Applied Dynamical Systems
Data Assimilation Nonlinear data Particle filters Proposal densities |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00113544 |
|
Leeuwen, Peter J. van
|
||
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||