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Data assimilation : inverse problems in dynamical systems

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Stuart, A. M. (2008) Data assimilation : inverse problems in dynamical systems. In: Conference on Monte Carlo Methods : Theory and Applications, Brown University, Providence, RI, 25-36 Apr 2008 (Unpublished)

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Official URL: http://www.dam.brown.edu/people/hhult/montecarlo/

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Abstract

Data assimilation is a subject whose genesis has been driven primarily by applied researchers in the atmospheric and geophysical sciences. At its heart is a very high dimensional inverse problem in dynamical systems. In order to reveal the inherent mathematical structure I will formulate this as a Bayesian inference problem on function space, and show that this problem is well-posed. I will then demonstrate how this formulation leads to the construction of efficient MCMC-based sampling methods. The basic idea underlying these methods is that MCMC methods defined on function space are robust under discretization.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Mathematics
Official Date: 25 April 2008
Dates:
DateEvent
25 April 2008Published
Status: Not Peer Reviewed
Publication Status: Unpublished
Version or Related Resource: Stuart, A. M. (2008). Data assimilation : inverse problems in dynamical systems. In: Numerical Modelling of Complex Dynamical Systems. Leiden, The Netherlands, 6-9 May 2008.
Conference Paper Type: Paper
Title of Event: Conference on Monte Carlo Methods : Theory and Applications
Type of Event: Conference
Location of Event: Brown University, Providence, RI
Date(s) of Event: 25-36 Apr 2008

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