Stochastic Optimal Prediction with Application to Averaged Euler Equations

Fuente: arXiv
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Main Authors: Bell, John, Chorin, Alexandre J., Crutchfield, William
Format: Preprint
Published: 2000
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author Bell, John
Chorin, Alexandre J.
Crutchfield, William
author_facet Bell, John
Chorin, Alexandre J.
Crutchfield, William
contents Optimal prediction (OP) methods compensate for a lack of resolution in the numerical solution of complex problems through the use of an invariant measure as a prior measure in the Bayesian sense. In first-order OP, unresolved information is approximated by its conditional expectation with respect to the invariant measure. In higher-order OP, unresolved information is approximated by a stochastic estimator, leading to a system of random or stochastic differential equations. We explain the ideas through a simple example, and then apply them to the solution of Averaged Euler equations in two space dimensions.
format Preprint
id arxiv_https___arxiv_org_abs_math_0008150
institution arXiv
publishDate 2000
record_format arxiv
spellingShingle Stochastic Optimal Prediction with Application to Averaged Euler Equations
Bell, John
Chorin, Alexandre J.
Crutchfield, William
Numerical Analysis
Optimal prediction (OP) methods compensate for a lack of resolution in the numerical solution of complex problems through the use of an invariant measure as a prior measure in the Bayesian sense. In first-order OP, unresolved information is approximated by its conditional expectation with respect to the invariant measure. In higher-order OP, unresolved information is approximated by a stochastic estimator, leading to a system of random or stochastic differential equations. We explain the ideas through a simple example, and then apply them to the solution of Averaged Euler equations in two space dimensions.
title Stochastic Optimal Prediction with Application to Averaged Euler Equations
topic Numerical Analysis
url https://arxiv.org/abs/math/0008150