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Related papers: Parametric family of SDEs driven by L\'evy noise

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In this article we show that a finite dimensional stochastic differential equation driven by a L\'evy process can be formulated as a stochastic partial differential equation. We prove the existence and uniqueness of strong solutions of such…

Probability · Mathematics 2018-02-15 Suprio Bhar , Rajeev Bhaskaran , Barun Sarkar

In this paper, we first explore certain structural properties of L\'evy flows and use this information to obtain the existence of strong solutions to a class of Stochastic PDEs in the space of tempered distributions, driven by L\'evy noise.…

Probability · Mathematics 2022-11-15 Arvind Kumar Nath , Suprio Bhar

We describe a class of explicit invariant measures for both finite and infinite dimensional Stochastic Differential Equations (SDE) driven by L\'evy noise. We first discuss in details the finite dimensional case with a linear, resp. non…

Probability · Mathematics 2014-07-16 Sergio Albeverio , Luca Di Persio , Elisa Mastrogiacomo , Boubaker Smii

We focus in this paper on the stochastic stabilization problems of PDEs by Levy noise. Sufficient conditions under which the perturbed systems decay exponentially with a general rate function are provided and some examples are constructed…

Probability · Mathematics 2011-04-15 Jianhai Bao , Chenggui Yuan

We consider a Stochastic Differential Equation driven by a L\'evy process whose L\'evy measure satisfy a tempered stable domination. We study how a perturbation of the coefficients reflects on the density of the solution. We quantify the…

Probability · Mathematics 2016-03-17 L Huang

Motivated by the results of \cite{sabanis2015}, we propose explicit Euler-type schemes for SDEs with random coefficients driven by L\'evy noise when the drift and diffusion coefficients can grow super-linearly. As an application of our…

Probability · Mathematics 2016-11-11 Chaman Kumar , Sotirios Sabanis

In this paper, the successive approximation method is applied to investigate the existence and uniqueness of solutions to the stochastic differential equations (SDEs) driven by L\'evy noise under non-Lipschitz condition which is a much…

Dynamical Systems · Mathematics 2014-05-15 Y Xu , B Pei

In Rajeev (2013), 'Translation invariant diffusion in the space of tempered distributions', it was shown that there is an one to one correspondence between solutions of a class of finite dimensional SDEs and solutions of a class of SPDEs in…

Probability · Mathematics 2016-05-26 Suprio Bhar

In this paper, we first show the well-posedness of the SDEs driven by L\'{e}vy noises under mild conditions. Then, we consider the existence and uniqueness of periodic solutions of the SDEs. To establish the ergodicity and uniqueness of…

Probability · Mathematics 2019-06-20 Xiao-Xia Guo , Wei Sun

In this article, we study the effects of the propagation of a non-degenerate L\'evy noise through a chain of deterministic differential equations whose coefficients are H\"older continuous and satisfy a weak H\"ormander-like condition. In…

Analysis of PDEs · Mathematics 2023-03-27 L. Marino , S. Menozzi

By a coupling method, we prove that a family of stochastic partial differential equations (SPDEs) driven by highly degenerate pure jump L\'evy noises are exponential mixing. These pure jump L\'evy noises include $\alpha$-stable process with…

Probability · Mathematics 2019-11-13 Xiaobin Sun , Yingchao Xie , Lihu Xu

In this article, we examine a stochastic partial differential equation (SPDE) driven by a symmetric $\alpha$-stable (S$\alpha$S) L\'evy noise, that is multiplied by a linear function $\sigma(u)=u$ of the solution. The solution is…

Probability · Mathematics 2024-09-20 Raluca M. Balan , Juan J. Jiménez

In this paper, we establish the existence of weak solutions for distribution-dependent stochastic differential equations (DDSDEs) driven by a broad class of L\'{e}vy noises, where the drift coefficients satisfy specific integrability…

Probability · Mathematics 2026-04-15 Mingkun Ye

We study a class of stochastic differential equations driven by a possibly tempered L{\'e}vy process, under mild conditions on the coefficients. We prove the well-posedness of the associated martingale problem as well as the existence of…

Probability · Mathematics 2016-02-01 L Huang

We study stochastic differential equations (SDEs) of McKean-Vlasov type with distribution dependent drifts and driven by pure jump L\'{e}vy processes. We prove a uniform in time propagation of chaos result, providing quantitative bounds on…

Probability · Mathematics 2020-11-10 Mingjie Liang , Mateusz B. Majka , Jian Wang

We prove the well-posedness of solutions to McKean-Vlasov stochastic differential equations driven by L\'evy noise under mild assumptions where, in particular, the L\'evy measure is not required to be finite. The drift, diffusion and jump…

Probability · Mathematics 2020-10-20 Neelima , Sani Biswas , Chaman Kumar , Gonçalo dos Reis , Christoph Reisinger

This paper studies stabilities of stochastic differential equation (SDE) driven by time-changed L\'evy noise in both probability and moment sense. This provides more flexibility in modeling schemes in application areas including physics,…

Probability · Mathematics 2016-04-27 Erkan Nane , Yinan Ni

We modify the coupling method established in [22, 20] and develop a technique to prove the exponential mixing of a 2D stochastic system forced by degenerate Levy noises. In particular, these Levy noises include $\alpha$-stable noises (0 <…

Probability · Mathematics 2015-01-27 Lihu Xu

The distributional support of the sample paths of L\'evy processes is an important issue for the construction of sparse statistical models, theories of integration in infinite dimensions and the existence of generalized solutions of…

Probability · Mathematics 2024-11-15 R. Vilela Mendes

Stochastic differential equations (SDEs) are a ubiquitous modeling framework that finds applications in physics, biology, engineering, social science, and finance. Due to the availability of large-scale data sets, there is growing interest…

Machine Learning · Statistics 2025-03-04 Ziheng Guo , James Greene , Ming Zhong
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