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An ensemble Kalman-Bucy filter for continuous data assimilation

  • The ensemble Kalman filter has emerged as a promising filter algorithm for nonlinear differential equations subject to intermittent observations. In this paper, we extend the well-known Kalman-Bucy filter for linear differential equations subject to continous observations to the ensemble setting and nonlinear differential equations. The proposed filter is called the ensemble Kalman-Bucy filter and its performance is demonstrated for a simple mechanical model (Langevin dynamics) subject to incremental observations of its velocity.

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Metadaten
Author:Kay Bergemann, Sebastian ReichORCiD
DOI:https://doi.org/10.1127/0941-2948/2012/0307
ISSN:0941-2948 (print)
Parent Title (English):Meteorologische Zeitschrift
Publisher:Schweizerbart
Place of publication:Stuttgart
Document Type:Article
Language:English
Year of first Publication:2012
Year of Completion:2012
Release Date:2017/03/26
Volume:21
Issue:3
Pagenumber:7
First Page:213
Last Page:219
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
Peer Review:Referiert