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SUMMARY:Data assimilation as an inverse problem: mathematical theory and c
 omputational challenges - Melina Freitag (University of Bath)
DTSTART:20130502T140000Z
DTEND:20130502T150000Z
UID:TALK42473@talks.cam.ac.uk
CONTACT:Carola-Bibiane Schoenlieb
DESCRIPTION:We provide a theoretical framework for data assimilation\, a s
 pecific type of inverse problem arising in numerical weather prediction\, 
 hydrology and geology. We show that data assimilation techniques such as t
 hree-dimensional and four-dimensional variational data assimilation (3DVar
  and 4DVar) as well as the Kalman filter and Bayes data assimilation are\,
  in the linear case\, merely a form of cycled Tikhonov regularisation. Fur
 thermore\, we provide an error analysis for the data assimilation process 
 in general. We then show that results from regularisation theory can be ap
 plied to data assimilation and give numerical examples.
LOCATION:MR 14\, CMS
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