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Bibliographic Details
Main Author: Gerencsér, Máté
Format: Preprint
Published: 2020
Subjects:
Online Access:https://arxiv.org/abs/2009.08418
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author Gerencsér, Máté
author_facet Gerencsér, Máté
contents We show that perturbing ill-posed differential equations with (potentially very) smooth random processes can restore well-posedness -- even if the perturbation is (potentially much) more regular than the drift component of the solution. The noise considered is of fractional Brownian type, and the familiar regularity condition $α>1-1/(2H)$ is recovered for all non-integer $H>1$.
format Preprint
id arxiv_https___arxiv_org_abs_2009_08418
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Regularisation by regular noise
Gerencsér, Máté
Probability
We show that perturbing ill-posed differential equations with (potentially very) smooth random processes can restore well-posedness -- even if the perturbation is (potentially much) more regular than the drift component of the solution. The noise considered is of fractional Brownian type, and the familiar regularity condition $α>1-1/(2H)$ is recovered for all non-integer $H>1$.
title Regularisation by regular noise
topic Probability
url https://arxiv.org/abs/2009.08418