Large deviations for stochastic flows of diffeomorphisms

Published 23 Feb 2010 in math.ST and stat.TH | (1002.4295v1)

Abstract: A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property is shown for the solution of an optimization problem involving the large deviations rate function.

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