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There is much confusion in the literature over Hurst exponent (H). The purpose of this paper is to illustrate the difference between fractional Brownian motion (fBm) on the one hand and Gaussian Markov processes where H is different to 1/2…

Signal Processing · Electrical Eng. & Systems 2021-03-10 G. Millán

There is much confusion in the literature over Hurst exponents. Recently, we took a step in the direction of eliminating some of the confusion. One purpose of this paper is to illustrate the difference between fBm on the one hand and…

Statistical Mechanics · Physics 2015-06-25 Joseph L. McCauley , Gemunu H. Gunaratne , Kevin E. Bassler

First, classes of Markov processes that scale exactly with a Hurst exponent H are derived in closed form. A special case of one class is the Tsallis density, advertised elsewhere as nonlinear diffusion or diffusion with nonlinear feedback.…

Physics and Society · Physics 2008-12-02 J. L. McCauley , G. H. Gunaratne , K. E. Bassler

Fractional Brownian motion is a Gaussian process x(t) with zero mean and two-time correlations <x(t)x(s)> ~ t^{2H} + s^{2H} - |t-s|^{2H}, where H, with 0<H<1 is called the Hurst exponent. For H = 1/2, x(t) is a Brownian motion, while for H…

Statistical Mechanics · Physics 2013-05-29 Kay Jörg Wiese , Satya N. Majumdar , Alberto Rosso

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

This paper investigates the probability distribution of solutions to McKean--Vlasov stochastic differential equations driven by fractional Brownian motion with Hurst parameter H>1/2. Our main contribution is the derivation of the associated…

Probability · Mathematics 2026-01-12 Saloua Labed , Nacira Agram , Bernt Oksendal

In this work, we prove a version of H\"{o}rmander's theorem for a stochastic evolution equation driven by a trace-class fractional Brownian motion with Hurst exponent $\frac{1}{2} < H < 1$ and an analytic semigroup on a given separable…

Probability · Mathematics 2020-03-19 Jorge A. de Nascimento , Alberto Ohashi

The paper suggests a way of stochastic integration of random integrands with respect to fractional Brownian motion with the Hurst parameter H> 1/2. The integral is defined initially on the processes that are "piecewise" predictable on a…

Probability · Mathematics 2020-04-21 Nikolai Dokuchaev

Fractional Brownian motion is a non-Markovian Gaussian process $X_t$, indexed by the Hurst exponent $H$. It generalises standard Brownian motion (corresponding to $H=1/2$). We study the probability distribution of the maximum $m$ of the…

Statistical Mechanics · Physics 2015-11-25 Mathieu Delorme , Kay Joerg Wiese

Given a fractional Brownian motion \,\,$(B_{t}^{H})_{t\geq 0}$,\, with Hurst parameter \,$> 1/2$\,\,we study the properties of all solutions of \,\,: {equation} X_{t}=B_{t}^{H}+\int_0^t X_{u}d\mu(u), \;\; 0\leq t\leq 1{equation} A different…

Probability · Mathematics 2011-07-20 Mamadou Abdoul Diop , Youssef Ouknine

We give a new representation of fractional Brownian motion with Hurst parameter H<=1/2 using stochastic partial differential equations. This representation allows us to use the Markov property and time reversal, tools which are not usually…

Probability · Mathematics 2012-01-31 Carl Mueller , Zhixin Wu

Fractional Brownian motion, a Gaussian non-Markovian self-similar process with stationary long-correlated increments, has been identified to give rise to the anomalous diffusion behavior in a great variety of physical systems. The…

We present results of the numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy tailed probability distribution functions. Assuming that the distribution function of the random fluctuations…

Statistical Mechanics · Physics 2017-08-16 Mohsen Ghasemi Nezhadhaghighi

In this paper we show that under some assumptions, for a $d$-dimensional fractional Brownian motion with Hurst parameter $H>1/2$, the density of solution of stochastic differential equation driven by it has a short-time expansion similar to…

Probability · Mathematics 2010-05-20 Fabrice Baudoin , Cheng Ouyang

The purpose of this comment is to correct mistaken assumptions and claims made in the paper Stochastic feedback, nonlinear families of Markov processes, and nonlinear Fokker-Planck equations by T. D. Frank. Our comment centers on the claims…

Statistical Mechanics · Physics 2009-11-13 Joseph L. McCauley

In this paper we introduce and analyze a class of diffusion type equations related to certain non-Markovian stochastic processes. We start from the forward drift equation which is made non-local in time by the introduction of a suitable…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Murad S. Taqqu , Francesco Mainardi

We consider the usual Langevin equation depending on an internal time. This parameter is substituted by a first passage time of a self-similar Markov process. Then the Gaussian process is parent, and the hitting time process is directing.…

Statistical Mechanics · Physics 2011-11-15 Aleksander Stanislavsky

We study fast / slow systems driven by a fractional Brownian motion $B$ with Hurst parameter $H\in (\frac 13, 1]$. Surprisingly, the slow dynamic converges on suitable timescales to a limiting Markov process and we describe its generator.…

Probability · Mathematics 2023-03-07 Martin Hairer , Xue-Mei Li

A class of Gaussian processes generalizing the usual fractional Brownian motion for Hurst indices in (1/2,1) and multifractal Brownian motion introduced in Ralchenko and Shevchenko (Theory Probab Math Stat 80, 2010) and Boufoussi et al.…

Probability · Mathematics 2013-07-08 Jelena Ryvkina

The long range dependence of the fractional Brownian motion (fBm), fractional Gaussian noise (fGn), and differentiated fGn (DfGn) is described by the Hurst exponent $H$. Considering the realisations of these three processes as time series,…

Data Analysis, Statistics and Probability · Physics 2016-07-20 Mariusz Tarnopolski
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