Large deviations for stochastic flows and their applications
type: Item
instance of: scholarly article
title: Large deviations for stochastic flows and their applications
zbMATH Open document ID: 1001.60061
DOI: 10.1007/BF02878977
published in: Science in China. Series A
publication date: 2002-08-15T00:00:00Z
review text: The large deviation principle (LDP) is established for stochastic flows looked upon as random variables valued in some smooth Banach space and, by using the Freidlin-Wentzell estimate and Sobolev's inequality, for stochastic flows considered as the ones valued in some Frechet space well-chosen for applying the composition principle of LDP given by \textit{A. Millet}, \textit{D. Nualart} and \textit{M. Sanz} [in: Stochastic analysis, 383-395 (1991; Zbl 0728.60028)]. A \(C_{p,r}\)-LDP for anticipating stochastic differential equations is given by the composition, too. The main tool for the establishment is to generalize classical results for diffusions.
Mathematics Subject Classification ID: 60H10
Mathematics Subject Classification ID: 35R60
Mathematics Subject Classification ID: 46N30
Mathematics Subject Classification ID: 60F10
Mathematics Subject Classification ID: 60H07
zbMATH DE Number: 1782143
zbMATH Keywords: large deviation
zbMATH Keywords: stochastic differential equation
zbMATH Keywords: stochastic flows
zbMATH Keywords: diffusion
zbMATH Keywords: capacity
zbMATH Keywords: anticipating stochastic differential equations
author: Fuqing Gao
author: Jiagang Ren
MaRDI profile type: Publication
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full work available at URL: https://doi.org/10.1007/bf02878977
OpenAlex ID: W2017797562
description: scientific article; zbMATH DE number 1782143