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We investigate in this work some situations where it is possible to estimate or determine the upper and the lower $q$-generalized fractal dimensions $D^{\pm}_{\mu}(q)$, $q\in\mathbb{R}$, of invariant measures associated with continuous…

Dynamical Systems · Mathematics 2019-10-15 Alexander Condori , Silas L. Carvalho

In an earlier work made by the first author with J. Turi (Degenerate Dirichlet Problems Related to the Invariant Measure of Elasto-Plastic Oscillators, AMO, 2008), the solution of a stochastic variational inequality modeling an…

Analysis of PDEs · Mathematics 2011-12-21 Alain Bensoussan , Laurent Mertz

We consider a stochastic conservation law on the line with solution-dependent diffusivity, a super-linear, sub-quadratic Hamiltonian, and smooth, spatially-homogeneous kick-type random forcing. We show that this Markov process admits a…

Probability · Mathematics 2023-08-29 Theodore D. Drivas , Alexander Dunlap , Cole Graham , Joonhyun La , Lenya Ryzhik

We describe a chain of unidirectionally coupled adaptive excitable elements slowly driven by a stochastic process from one end and open at the other end, as a minimal toy model of unresolved irreducible uncertainty in a system performing…

Neurons and Cognition · Quantitative Biology 2022-09-14 Mario Martinez-Saito

Let $\Sigma$ be a finite alphabet, $\Omega=\Sigma^{\mathbb{Z}^{d}}$ equipped with the shift action, and $\mathcal{I}$ the simplex of shift-invariant measures on $\Omega$. We study the relation between the restriction $\mathcal{I}_n$ of…

Dynamical Systems · Mathematics 2011-09-21 J. -R. Chazottes , J. -M. Gambaudo , M. Hochman , E. Ugalde

In this paper, we introduce a novel Extra-Gradient method with anchor term governed by general parameters. Our method is derived from an explicit discretization of a Tikhonov-regularized monotone flow in Hilbert space, which provides a…

Optimization and Control · Mathematics 2024-10-21 Radu Ioan Boţ , Enis Chenchene

In this paper, we consider the classical spin systems on unbounded lattices given by infinite-dimensional stochastic differential equations (SDEs). We assume that the stochastic forcing acts only on one particle. The other particles are not…

Probability · Mathematics 2026-04-16 Tong Lu , Huaizhong Zhao

Continuous Time Markov Chains, Hawkes processes and many other interesting processes can be described as solution of stochastic differential equations driven by Poisson measures. Previous works, using the Stein's method, give the…

Probability · Mathematics 2026-04-02 Eustache Besançon , Laure Coutin , Laurent Decreusefond , Pascal Moyal

We study the limiting behavior of continuous time trawl processes which are defined using an infinitely divisible random measure of a time dependent set. In this way one is able to define separately the marginal distribution and the…

Probability · Mathematics 2017-08-10 Danijel Grahovac , Nikolai N. Leonenko , Murad S. Taqqu

We introduce a class of discrete random walk model driven by global memory effects. At any time the right-left transitions depend on the whole previous history of the walker, being defined by an urn-like memory mechanism. The characteristic…

Statistical Mechanics · Physics 2016-12-28 Adrian A. Budini

In this paper, we study ergodic backward stochastic differential equations (EBSDEs for short), for which the underlying diffusion is assumed to be multiplicative and of at most linear growth. The fact that the forward process has an…

Probability · Mathematics 2018-01-08 Ying Hu , Florian Lemonnier

We introduce and study a class of determinantal probability measures generalising the class of discrete determinantal point processes. These measures live on the Grassmannian of a real, complex, or quaternionic inner product space that is…

Probability · Mathematics 2023-08-22 Adrien Kassel , Thierry Lévy

We derive consistency and asymptotic normality results for quasi-maximum likelihood methods for drift parameters of ergodic stochastic processes observed in discrete time in an underlying continuous-time setting. The special feature of our…

Statistics Theory · Mathematics 2021-09-20 Teppei Ogihara , Mitja Stadje

We consider eigenvalues of generalized Wishart processes as well as particle systems, of which the empirical measures converge to deterministic measures as the dimension goes to infinity. In this paper, we obtain central limit theorems to…

Probability · Mathematics 2019-08-12 Jian Song , Jianfeng Yao , Wangjun Yuan

In this paper, we construct the wavelet eigenvalue regression methodology in high dimensions. We assume that possibly non-Gaussian, finite-variance $p$-variate measurements are made of a low-dimensional $r$-variate ($r \ll p$) fractional…

Statistics Theory · Mathematics 2022-08-01 Patrice Abry , B. Cooper Boniece , Gustavo Didier , Herwig Wendt

We study some SDEs derived from the $q\to 1$ limit of a 2D surface growth model called the $q$-Whittaker process. The fluctuations are proven to exhibit Gaussian characteristics that "come down from infinity": After rescaling and…

Probability · Mathematics 2021-01-12 Yu-Ting Chen

We develop a gradient-flow theory for time-dependent functionals defined in abstract metric spaces. Global well-posedness and asymptotic behavior of solutions are provided. Conditions on functionals and metric spaces allow to consider the…

Analysis of PDEs · Mathematics 2015-09-15 Lucas C. F. Ferreira , Julio C. Valencia-Guevara

For an ergodic hyperbolic measure $\omega$ of a $C^{1+{\alpha}}$ diffeomorphism, there is an $\omega$ full-measured set $\tilde\Lambda$ such that every nonempty, compact and connected subset $V$ of $\mathbb{M}_{inv}(\tilde\Lambda)$…

Dynamical Systems · Mathematics 2013-03-07 Chao Liang , Wenxiang Sun , Xueting Tian

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

We derive high-dimensional scaling limits and fluctuations for the online least-squares Stochastic Gradient Descent (SGD) algorithm by taking the properties of the data generating model explicitly into consideration. Our approach treats the…

Probability · Mathematics 2024-04-05 Krishnakumar Balasubramanian , Promit Ghosal , Ye He
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