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arXiv 0907.0253math.PR
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时变Lévy过程驱动的随机微分方程及其时间分数阶伪微分方程

SDEs driven by a time-changed Lévy process and their associated time-fractional order pseudo-differential equations

Marjorie G. Hahn, Kei Kobayashi, Sabir Umarov

摘要:

已知经典伊藤随机微分方程解的转移概率在弱意义下满足Kolmogorov方程. Kolmogorov方程是一个系数由相应的ε决定的偏微分方程。时间分数阶Kolmogorov型方程在许多领域被用来模拟复杂过程。然而,除了少数特殊情况外,与这些方程相关联的一类SDES是未知的。本文表明,无论是时间分数阶或更一般的时间分布阶微分方程的情况下,相关类的SDES可以在半鞅驱动的SDES的框架内描述。这些半鞅是时变Lévy过程,其中独立时变分别由单个或混合独立稳定从属子的逆给出。提供的例子,包括一个分数类似的费曼-卡茨公式。

英文摘要:

It is known that the transition probabilities of a solution to a classical Itô stochastic differential equation (SDE) satisfy in the weak sense the associated Kolmogorov equation. The Kolmogorov equation is a partial differential equation with coeffcients determined by the corresponding SDE. Time-fractional Kolmogorov type equations are used to model complex processes in many fields. However, the class of SDEs that is associated with these equations is unknown except in a few special cases. The present paper shows that in the cases of either time-fractional order or more general time-distributed order differential equations, the associated class of SDEs can be described within the framework of SDEs driven by semimartingales. These semimartingales are time-changed Lévy processes where the independent time-change is given respectively by the inverse of a single or mixture of independent stable subordinators. Examples are provided, including a fractional analogue of the Feynman-Kac formula.

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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