Riemann-Liouville fractional Brownian motion with random Hurst exponent.

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED Chaos Pub Date : 2025-02-01 DOI:10.1063/5.0243975
Hubert Woszczek, Agnieszka Wyłomańska, Aleksei Chechkin
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Abstract

We examine two stochastic processes with random parameters, which in their basic versions (i.e., when the parameters are fixed) are Gaussian and display long-range dependence and anomalous diffusion behavior, characterized by the Hurst exponent. Our motivation comes from biological experiments, which show that the basic models are inadequate for accurate description of the data, leading to modifications of these models in the literature through introduction of the random parameters. The first process, fractional Brownian motion with random Hurst exponent (referred to as FBMRE below) has been recently studied, while the second one, Riemann-Liouville fractional Brownian motion with random exponent (RL FBMRE) has not been explored. To advance the theory of such doubly stochastic anomalous diffusion models, we investigate the probabilistic properties of RL FBMRE and compare them to those of FBMRE. Our main focus is on the autocovariance function and the time-averaged mean squared displacement of the processes. Furthermore, we analyze the second moment of the increment processes for both models, as well as their ergodicity properties. As a specific case, we consider the mixture of two-point distributions of the Hurst exponent, emphasizing key differences in the characteristics of RL FBMRE and FBMRE, particularly in their asymptotic behavior. The theoretical findings presented here lay the groundwork for developing new methods to distinguish these processes and estimate their parameters from experimental data.

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随机Hurst指数的Riemann-Liouville分数布朗运动。
我们研究了两个具有随机参数的随机过程,它们在其基本版本(即,当参数固定时)是高斯的,并表现出远程依赖和异常扩散行为,以Hurst指数为特征。我们的动机来自于生物学实验,实验表明基本模型不足以准确描述数据,导致文献中通过引入随机参数对这些模型进行修改。第一个过程,随机赫斯特指数分数布朗运动(以下简称FBMRE)最近得到了研究,而第二个过程,随机指数Riemann-Liouville分数布朗运动(RL FBMRE)尚未探索。为了提出这种双随机异常扩散模型的理论,我们研究了RL FBMRE的概率性质,并将其与FBMRE的概率性质进行了比较。我们的主要重点是自协方差函数和过程的时间平均均方位移。进一步,我们分析了两种模型的增量过程的二阶矩,以及它们的遍历性。作为一个具体的例子,我们考虑了Hurst指数的两点分布的混合,强调了RL FBMRE和FBMRE在特征上的关键区别,特别是在它们的渐近行为上。本文提出的理论发现为开发新的方法来区分这些过程并从实验数据中估计其参数奠定了基础。
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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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