Calculating the Malliavin derivative of one stochastic mechanics problem
The Malliavin weight sampling method is a way to tracking the dynamics of a stochastic system. In this FYP, we aim to apply this MWS method to a specific stochastic problem. First, we construct a Malliavin weight in a rigorous and precise mathematical way. Then we apply this MWS to Kelvin-Voigt stoc...
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sg-ntu-dr.10356-1364812023-02-28T23:13:47Z Calculating the Malliavin derivative of one stochastic mechanics problem Lyu, Xingyu Nicolas Privault School of Physical and Mathematical Sciences NPRIVAULT@ntu.edu.sg Science Science::Mathematics::Probability theory The Malliavin weight sampling method is a way to tracking the dynamics of a stochastic system. In this FYP, we aim to apply this MWS method to a specific stochastic problem. First, we construct a Malliavin weight in a rigorous and precise mathematical way. Then we apply this MWS to Kelvin-Voigt stochastic model with Gaussian random variable to study the dynamic of the system with respect to some parameter in the system. We found that the dynamic of the system can be approximated by MWS method perfectly when time is close to zero and the Malliavin weight deviates from the analytical solution when time becomes larger. Then we verified this result by a numerical approximation by Euler’s explicit finite difference method. This FYP is a supplementary work for existing study on Malliavin sampling method regarding the dynamic of the Malliavin weight, especially in Kelvin-Voigt model. Bachelor of Science in Mathematical Sciences and Economics 2019-12-19T02:53:42Z 2019-12-19T02:53:42Z 2019 Final Year Project (FYP) https://hdl.handle.net/10356/136481 en application/pdf Nanyang Technological University |
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Science Science::Mathematics::Probability theory Lyu, Xingyu Calculating the Malliavin derivative of one stochastic mechanics problem |
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The Malliavin weight sampling method is a way to tracking the dynamics of a stochastic system. In this FYP, we aim to apply this MWS method to a specific stochastic problem. First, we construct a Malliavin weight in a rigorous and precise mathematical way. Then we apply this MWS to Kelvin-Voigt stochastic model with Gaussian random variable to study the dynamic of the system with respect to some parameter in the system. We found that the dynamic of the system can be approximated by MWS method perfectly when time is close to zero and the Malliavin weight deviates from the analytical solution when time becomes larger. Then we verified this result by a numerical approximation by Euler’s explicit finite difference method. This FYP is a supplementary work for existing study on Malliavin sampling method regarding the dynamic of the Malliavin weight, especially in Kelvin-Voigt model. |
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Nicolas Privault |
author_facet |
Nicolas Privault Lyu, Xingyu |
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Final Year Project |
author |
Lyu, Xingyu |
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Lyu, Xingyu |
title |
Calculating the Malliavin derivative of one stochastic mechanics problem |
title_short |
Calculating the Malliavin derivative of one stochastic mechanics problem |
title_full |
Calculating the Malliavin derivative of one stochastic mechanics problem |
title_fullStr |
Calculating the Malliavin derivative of one stochastic mechanics problem |
title_full_unstemmed |
Calculating the Malliavin derivative of one stochastic mechanics problem |
title_sort |
calculating the malliavin derivative of one stochastic mechanics problem |
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Nanyang Technological University |
publishDate |
2019 |
url |
https://hdl.handle.net/10356/136481 |
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1759854811114635264 |