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Related papers: Fractional Gaussian fields: a survey

200 papers

In the framework of metric-like approach, totally symmetric arbitrary spin bosonic conformal fields propagating in flat space-time are studied. Depending on the values of conformal dimension, spin, and dimension of space-time, we classify…

High Energy Physics - Theory · Physics 2016-07-20 R. R. Metsaev

Here, we provide a unified framework for numerical analysis of stochastic nonlinear fractional diffusion equation driven by fractional Gaussian noise with Hurst index $H\in(0,1)$. A novel estimate of the second moment of the stochastic…

Numerical Analysis · Mathematics 2021-04-29 Daxin Nie , Weihua Deng

Additive or multiplicative stationary noise recently became an important issue in applied fields such as microscopy or satellite imaging. Relatively few works address the design of dedicated denoising methods compared to the usual white…

Computer Vision and Pattern Recognition · Computer Science 2013-07-18 Jérôme Fehrenbach , Pierre Weiss

Fractional Gaussian fields provide a rich class of spatial models and have a long history of applications in multiple branches of science. However, estimation and inference for fractional Gaussian fields present significant challenges. This…

Methodology · Statistics 2022-02-22 Somak Dutta , Debashis Mondal

We find the best approximation of the fractional Brownian motion with the Hurst index $H\in (0,1/2)$ by Gaussian martingales of the form $\int _0^ts^{\gamma}dW_s$, where $W$ is a Wiener process, $\gamma >0$.

Probability · Mathematics 2020-06-29 Oksana Banna , Filipp Buryak , Yuliya Mishura

The aim of the paper is to show the probabilistically strong well-posedness of rough differential equations with distributional drifts driven by the Gaussian rough path lift of fractional Brownian motion with Hurst parameter…

Probability · Mathematics 2024-12-17 Konstantinos Dareiotis , Máté Gerencsér , Khoa Lê , Chengcheng Ling

This work brings together two powerful concepts in Gaussian processes: the variational approach to sparse approximation and the spectral representation of Gaussian processes. This gives rise to an approximation that inherits the benefits of…

Machine Learning · Statistics 2017-11-09 James Hensman , Nicolas Durrande , Arno Solin

We consider a two parameter family of unitarily invariant diffusion processes on the general linear group $\mathbb{GL}_N$ of $N\times N$ invertible matrices, that includes the standard Brownian motion as well as the usual unitary Brownian…

Probability · Mathematics 2015-06-23 Guillaume Cébron , Todd Kemp

In this article, we consider the following stochastic fractional diffusion equation \begin{equation*} \left(\partial^{\beta}+\dfrac{\nu}{2}\left(-\Delta\right)^{\alpha / 2}\right) u(t, x)= \lambda\: I_{0_+}^{\gamma}\left[u(t, x) \dot{W}(t,…

Probability · Mathematics 2023-03-22 Yuhui Guo , Jian Song , Xiaoming Song

In this paper, we investigate large-scale linear systems driven by a fractional Brownian motion (fBm) with Hurst parameter $H\in [1/2, 1)$. We interpret these equations either in the sense of Young ($H>1/2$) or Stratonovich ($H=1/2$).…

Numerical Analysis · Mathematics 2026-04-01 Nahid Jamshidi , Martin Redmann

We consider the class of selfsimilar Gaussian generalized random fields introduced by Dobrushin in 1979. These fields are indexed by Schwartz functions on $\mathbb{R}^d$ and parametrized by a self-similarity index and the degree of…

Probability · Mathematics 2014-10-03 Maik Görgens , Ingemar Kaj

Normal inverse Gaussian (NIG) process was introduced by Barndorff-Nielsen (1997) by subordinating Brownian motion with drift to an inverse Gaussian process. Increments of NIG process are independent and stationary. In this paper, we…

Probability · Mathematics 2009-07-22 Arun Kumar , P. Vellaisamy

This paper presents finite-velocity random motions driven by fractional Klein-Gordon equations of order $\alpha \in (0,1]$. A key tool in the analysis is played by the McBride's theory which converts fractional hyper-Bessel operators into…

Probability · Mathematics 2014-07-01 Roberto Garra , Enzo Orsingher , Federico Polito

Spartan Spatial Random Fields (SSRFs) are generalized Gibbs random fields, equipped with a coarse-graining kernel that acts as a low-pass filter for the fluctuations. SSRFs are defined by means of physically motivated spatial interactions…

Information Theory · Computer Science 2012-04-12 Dionissios T. Hristopulos , Samuel Elogne

We describe two classes of Gaussian self-similar random fields: with strictly stationary rectangular increments and with mild stationary rectangular increments. We find explicit spectral and moving average representations for the fields…

Probability · Mathematics 2019-04-02 Vitalii Makogin , Yuliya Mishura

We propose a new algorithm to generate a fractional Brownian motion, with a given Hurst parameter, 1/2<H<1 using the correlated Bernoulli random variables with parameter p; having a certain density. This density is constructed using the…

Computation · Statistics 2019-05-15 Buket Coskun , Ceren Vardar-Acar , Hakan Demirtas

Fractional Brownian motion (fBm) is an important scale-invariant Gaussian non-Markovian process with stationary increments, which serves as a prototypical example of a system with long-range temporal correlations and anomalous diffusion.…

Statistical Mechanics · Physics 2026-04-29 Baruch Meerson , Pavel V. Sasorov

Fractional Brownian motion is a non-Markovian Gaussian process indexed by the Hurst exponent $H\in [0,1]$, generalising standard Brownian motion to account for anomalous diffusion. Functionals of this process are important for practical…

Statistical Mechanics · Physics 2021-11-24 Tridib Sadhu , Kay Jörg Wiese

In this note we prove that the Fourier dimension of the graph $G(B)$ of a fractional Brownian motion $B$ with Hurst parameter $H\in(0,1/2)$ is equal to 1. This finishes to solve a conjecture by Fraser and Sahlsten. It also yields an exact…

Probability · Mathematics 2025-10-14 Cheuk Yin Lee , Samy Tindel

This work is concerned with fractional Gaussian fields, i.e. Gaussian fields whose covariance operator is given by the inverse fractional Laplacian $(-\Delta)^{-s}$ (where, in particular, we include the case $s >1$). We define a lattice…

Probability · Mathematics 2025-06-17 Nicola De Nitti , Florian Schweiger