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Large Deviations for a Class of Anticipating Stochastic Differential Equations
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1992
Year
Large DeviationsEngineeringUncertainty QuantificationRandom VectorsStochastic ProcessesIntegrable ProbabilityStochastic CalculusLarge Deviations EstimatesStochastic Dynamical SystemStochastic SystemStochastic AnalysisProbability TheoryStochastic PhenomenonFunctional AnalysisCanonical SpaceStochastic Differential EquationStatisticsStochastic Differential Equations
Consider the family of perturbed stochastic differential equations on $\mathbb{R}^d$, $X^\varepsilon_t = X^\varepsilon_0 + \sqrt{\varepsilon} \int^t_0\sigma(X^\varepsilon_s)\circ dW_s + \int^t_0 b(X^\varepsilon_s) ds,$ $\varepsilon > 0$, defined on the canonical space associated with the standard $k$-dimensional Wiener process $W$. We assume that $\{X^\varepsilon_0, \varepsilon > 0\}$ is a family of random vectors not necessarily adapted and that the stochastic integral is a generalized Stratonovich integral. In this paper we prove large deviations estimates for the laws of $\{X^\varepsilon_., \varepsilon > 0\}$, under some hypotheses on the family of initial conditions $\{X^\varepsilon_0, \varepsilon > 0\}$.