Qi Zhang
Probabilistic representation of weak solutions of partial differential equations with polynomial growth coefficients
Zhang, Qi; Zhao, Huaizhong
Abstract
In this paper we develop a new weak convergence and compact embedding method to study the existence and uniqueness of the L2p
ρ (Rd ;R1)×L2ρ(Rd ;Rd ) valued solution of backward stochastic differential equations with p-growth coefficients.
Then we establish the probabilistic representation of the weak solution of PDEs with p-growth coefficients via corresponding BSDEs.
Citation
Zhang, Q., & Zhao, H. (2012). Probabilistic representation of weak solutions of partial differential equations with polynomial growth coefficients. Journal of Theoretical Probability, 25, 396–423. https://doi.org/10.1007/s10959-011-0350-y
Journal Article Type | Article |
---|---|
Online Publication Date | Mar 17, 2011 |
Publication Date | 2012-06 |
Deposit Date | Oct 6, 2021 |
Journal | Journal of Theoretical Probability |
Print ISSN | 0894-9840 |
Electronic ISSN | 1572-9230 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 25 |
Pages | 396–423 |
DOI | https://doi.org/10.1007/s10959-011-0350-y |
Public URL | https://durham-repository.worktribe.com/output/1237214 |
You might also like
Periodic measures and Wasserstein distance for analysing periodicity of time series datasets
(2023)
Journal Article
Local Time Rough Path for Lévy Processes
(2010)
Journal Article
Two-parameter p, q-variation Paths and Integrations of Local Times
(2006)
Journal Article
Numerical approximation of random periodic solutions of stochastic differential equations
(2017)
Journal Article
A Generalized Ito's Formula in Two-Dimensions and Stochastic Lebesgue-Stieltjes Integrals
(2007)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search