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Morphing Ensemble Kalman Filters | | Jonathan D. Beezley
; Jan Mandel
; | | Date: |
27 May 2007 | | Subject: | Dynamical Systems (math.DS); Computer Vision and Pattern Recognition (cs.CV); Statistics (math.ST); Atmospheric and Oceanic Physics (physics.ao-ph) | | Abstract: | A new type of ensemble filter is proposed, which combines an ensemble Kalman
filter (EnKF) with the ideas of morphing and registration from image
processing. This results in filters suitable for nonlinear problems whose
solutions exhibit moving coherent features, such as thin interfaces in wildfire
modeling. The ensemble members are represented as the composition of one common
state with a spatial transformation, called registration mapping, plus a
residual. A fully automatic registration method is used that requires only
gridded data, so the features in the model state do not need to be identified
by the user. The morphing EnKF operates on a transformed state consisting of
the registration mapping and the residual. Essentially, the morphing EnKF uses
intermediate states obtained by morphing instead of linear combinations of the
states. | | Source: | arXiv, arxiv.0705.3693 | | Services: | Forum | Review | PDF | Favorites | |
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