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Set-valued and fuzzy stochastic integral equations driven by semimartingales under Osgood condition : Open Mathematics

机译:在Osgood条件下由半driven驱动的集值和模糊随机积分方程:开放数学

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摘要

We analyze the set-valued stochastic integral equations driven by continuous semimartingales and prove the existence and uniqueness of solutions to such equations in the framework of the hyperspace of nonempty, bounded, convex and closed subsets of the Hilbert space L2 (consisting of square integrable random vectors). The coefficients of the equations are assumed to satisfy the Osgood type condition that is a generalization of the Lipschitz condition. Continuous dependence of solutions with respect to data of the equation is also presented. We consider equations driven by semimartingale Z and equations driven by processes A;M from decomposition of Z, where A is a process of finite variation and M is a local martingale. These equations are not equivalent. Finally, we show that the analysis of the set-valued stochastic integral equations can be extended to a case of fuzzy stochastic integral equations driven by semimartingales under Osgood type condition. To obtain our results we use the set-valued and fuzzy Maruyama type approximations and Bihari’s inequality.
机译:我们分析了由连续半mart驱动的集值随机积分方程,并证明了这些方程在Hilbert空间L2的非空,有界,凸和闭子集的超空间(由平方可积随机随机数)构成的超空间框架内的存在性和唯一性向量)。假设方程式的系数满足作为Lipschitz条件的推广的Osgood类型条件。还提出了关于方程数据的解的连续依赖性。我们考虑由半mart Z驱动的方程和由Z分解产生的过程A; M驱动的方程,其中A是有限变化的过程,M是局部mar。这些方程式不是等效的。最后,我们证明了在Osgood型条件下,集值随机积分方程的分析可以扩展到半semi驱动的模糊随机积分方程的情况。为了获得我们的结果,我们使用集值模糊Maruyama型近似和Bihari不等式。

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