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Fuzzy stochastic differential equations of decreasing fuzziness: Non-Lipschitz coefficients

机译:降低模糊性的模糊随机微分方程:非Lipschitz系数

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摘要

We study fuzzy stochastic differential equations driven by multidimensional Brownian motion with solutions of decreasing fuzziness. The drift and diffusion coefficients are random. Under a non-Lipschitz condition, the existence and pathwise uniqueness of solutions to such the equations are proven. The solutions are considered to be fuzzy stochastic processes. The main result is obtained with a help of a sequence of approximate solutions that converge to a desired unique local solution with trajectories having decreasing fuzziness. A parallel assertion for solutions to fuzzy stochastic differential equations of increasing fuzziness is stated as well. We indicate that our considerations of fuzzy stochastic differential equations of decreasing fuzziness can be applied to examine non-Lipschitz set-valued stochastic differential equations with solutions being set-valued stochastic processes.
机译:我们研究了由多维布朗运动驱动的模糊随机微分方程,并具有降低模糊性的解决方案。漂移和扩散系数是随机的。在非Lipschitz条件下,证明了此类方程解的存在性和路径唯一性。解决方案被认为是模糊随机过程。主要结果是借助于一系列近似解的帮助而获得的,这些近似解收敛到具有减少的模糊性的轨迹的所需唯一局部解。还提出了一个关于增加模糊性的模糊随机微分方程解的并行断言。我们指出,我们对降低模糊性的模糊随机微分方程的考虑可以用于检验非Lipschitz集值随机微分方程,其解为集值随机过程。

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