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arXiv math/0610178math.PR
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随机微分方程弱逼近的对偶方法

A duality approach for the weak approximation of stochastic differential equations

Emmanuelle Clément, Arturo Kohatsu-Higa, Damien Lamberton

摘要:

在这篇文章中,我们发展了一种新的方法来证明一般随机微分方程的弱逼近结果。代替使用偏微分方程的方法,通常是做的扩散,这里考虑的方法使用的线性方程满足的误差过程的属性。这种方法似乎适用于一大类过程,我们作为一个例子,随机延迟方程的弱近似。

英文摘要:

In this article we develop a new methodology to prove weak approximation results for general stochastic differential equations. Instead of using a partial differential equation approach as is usually done for diffusions, the approach considered here uses the properties of the linear equation satisfied by the error process. This methodology seems to apply to a large class of processes and we present as an example the weak approximation of stochastic delay equations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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