Large deviations for stochastic flows of diffeomorphisms

被引：27

作者：

Budhiraja, Amarjit ^{[1
]}

Dupuis, Paul ^{[2
]}

Maroulas, Vasileios ^{[3
]}

机构：

[1] Univ N Carolina, Dept Stat & Operat Res, Chapel Hill, NC 27599 USA

[2] Brown Univ, Div Appl Math, Providence, RI 02912 USA

[3] Univ Minnesota, Inst Math & Applicat, Minneapolis, MN 55455 USA

来源：

BERNOULLI | 2010年 / 16卷 / 01期

基金：

美国国家科学基金会;

关键词：

deformable templates; diffeomorphisrns; image matching; infinite-dimensional Brownian motion; infinite-dimensional SDEs; large deviations; semimartingales with a spatial parameter; small noise asymptotics; stochastic flows; DIFFERENTIAL-EQUATIONS; SYSTEMS;

D O I：

10.3150/09-BEJ203

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：234 / 257

页数：24

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