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Herein we develop a dynamical foundation for fractional Brownian Motion. A clear relation is established between the asymptotic behaviour of the correlation function and diffusion in a dynamical system. Then, assuming that scaling is…

chao-dyn · Physics 2008-02-03 R Mannella , P Grigolini , BJ West

In a previous paper, we studied the ergodic properties of an Euler scheme of a stochastic differential equation with a Gaussian additive noise in order to approximate the stationary regime of such equation. We now consider the case of…

Probability · Mathematics 2013-11-20 Serge Cohen , Fabien Panloup , Samy Tindel

We present the expansion of the multifractional Brownian (mBm) local time in higher dimensions, in terms of Wick powers of white noises (or multiple Wiener integrals). If a suitable number of kernels is subtracted, they exist in the sense…

Probability · Mathematics 2018-11-19 Wolfgang Bock , Jose Luis da Silva , Herry Pribawanto Suryawan

We consider the dynamics of the stochastic shadow Gierer-Meinhardt system with one-dimensional standard Brownian motion. We establish the global existence and uniqueness of solutions. We also prove a large deviation result.

Probability · Mathematics 2014-02-21 M. Winter , L. Xu , J. Zhai , T. Zhang

In this note we prove that the probability measures generated by two generalized grey Brownian motions with different parameters are singular with respect to each other. This result can be interpreted as an extension of the Feldman-H\'ajek…

Probability · Mathematics 2018-11-19 José Luís da Silva , Mohamed Erraoui

In this paper, we construct operator fractional L\'evy motion (ofLm), a broad class of non-Gaussian stochastic processes that are covariance operator self-similar, have wide-sense stationary increments and display infinitely divisible…

Probability · Mathematics 2021-06-17 Benjamin Cooper Boniece , Gustavo Didier

The scaled Brownian motion (SBM) is regarded as one of the paradigmatic random processes, featuring the anomalous diffusion property characterized by the diffusion exponent. It is a Gaussian, self-similar process with independent…

Probability · Mathematics 2024-04-29 Hubert Woszczek , Aleksei Chechkin , Agnieszka Wylomanska

In this paper, we consider the statistical inference of the drift parameter $\theta$ of non-ergodic Ornstein-Uhlenbeck~(O-U) process driven by a general Gaussian process $(G_t)_{t\ge 0}$. When $H \in (0, \frac 12) \cup (\frac 12,1) $ the…

Statistics Theory · Mathematics 2022-07-28 Yanping Lu

In this paper we introduce the long-range dependent completely correlated mixed fractional Brownian motion (ccmfBm). This is a process that is driven by a mixture of Brownian motion (Bm) and a long-range dependent completely correlated…

Probability · Mathematics 2021-09-14 Josephine Dufitinema , Foad Shokrollahi , Tommi Sottinen , Lauri Viitasaari

The generalized fractional Brownian motion (GFBM) $X:=\{X(t)\}_{t\ge0}$ with parameters $\gamma \in [0, 1)$ and $\alpha\in \left(-\frac12+\frac{\gamma}{2}, \, \frac12+\frac{\gamma}{2} \right)$ is a centered Gaussian $H$-self-similar process…

Probability · Mathematics 2021-08-10 Ran Wang , Yimin Xiao

This paper is concerned with the stochastic thermodynamics of non-equilibrium Gaussian processes that can exhibit anomalous diffusion. In the systems considered, the noise correlation function is not necessarily related to friction. Thus,…

Statistical Mechanics · Physics 2022-12-20 S. Mohsen J. Khadem , Rainer Klages , Sabine H. L. Klapp

It is classical to approximate the distribution of fractional Brownian motion by a renormalized sum $ S_n $ of dependent Gaussian random variables. In this paper we consider such a walk $ Z_n $ that collects random rewards $ \xi_j $ for $ j…

Probability · Mathematics 2008-12-18 Serge Cohen , Clément Dombry

Stochastic Gradient Langevin Dynamics (SGLD) is a sampling scheme for Bayesian modeling adapted to large datasets and models. SGLD relies on the injection of Gaussian Noise at each step of a Stochastic Gradient Descent (SGD) update. In this…

Machine Learning · Computer Science 2018-06-11 Henri Palacci , Henry Hess

In this paper we obtain Gaussian-type lower bounds for the density of solutions to stochastic differential equations (SDEs) driven by a fractional Brownian motion with Hurst parameter $H$. In the one-dimensional case with additive noise,…

Probability · Mathematics 2016-08-11 M. Besalú , A. Kohatsu-Higa , S. Tindel

In this paper, we show that the integration of a stochastic differential equations driven by G-Brownian motion in R can be reduced to the integration of an ordinary differential equations parametrized by a variable in ({\Omega},F). We study…

Probability · Mathematics 2014-09-02 Peng Luo , Falei Wang

We study a particular generalisation of the classical Kramers model describing Brownian particles in the external potential. The generalised model includes the stochastic force which is modelled as an additive random noise that depends upon…

Statistical Mechanics · Physics 2010-09-09 Vlad Bezuglyy

Recently a procedure by generalized density matrix (GDM) is proposed for calculating a collective/bosonic Hamiltonian microscopically from the shell-model Hamiltonian. In this work we examine the validity of the method by comparing the GDM…

Nuclear Theory · Physics 2015-06-04 L. Y. Jia , V. G. Zelevinsky

We develope a computationally efficient extension of the Dyson Brownian Motion (DBM) algorithm to generate random function in C2 locally. We further explain that random functions generated via DBM show an unstable growth as the traversed…

High Energy Physics - Theory · Physics 2016-09-09 Gaoyuan Wang , Thorsten Battefeld

A theory for (1+3)-dimensional relativistic Brownian motion under the influence of external force fields is put forward. Starting out from a set of relativistically covariant, but multiplicative Langevin equations we describe the…

Statistical Mechanics · Physics 2009-11-11 Jörn Dunkel , Peter Hänggi

Closed-form expressions, parametrized by the Hurst exponent $H$ and the length $n$ of a time series, are derived for paths of fractional Brownian motion (fBm) and fractional Gaussian noise (fGn) in the $\mathcal{A}-\mathcal{T}$ plane,…

Data Analysis, Statistics and Probability · Physics 2020-01-01 Mariusz Tarnopolski
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