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We construct a wavelet and a generalised Fourier basis with respect to some fractal measures given by one-dimensional iterated function systems. In this paper we will not assume that these systems are given by linear contractions…

Functional Analysis · Mathematics 2010-06-30 Jana Bohnstengel , Marc Kesseböhmer

The limiting behavior of Toeplitz type quadratic forms of stationary processes has received much attention through decades, particularly due to its importance in statistical estimation of the spectrum. In the present paper we study such…

Probability · Mathematics 2018-08-20 Mikkel Slot Nielsen , Jan Pedersen

We study the least squares estimator for the drift parameter of the Langevin stochastic equation driven by the Rosenblatt process. Using the techniques of the Malliavin calculus and the stochastic integration with respect to the Rosenblatt…

Probability · Mathematics 2019-03-07 Radomyra Shevchenko , Ciprian A. Tudor

The nonlinear dynamics of an obliquely oriented wave packet at sea surface is studied both analytically and numerically for various initial parameters of the packet, in connection with the problem of oceanic rogue waves. In the framework of…

Fluid Dynamics · Physics 2015-04-10 V. P. Ruban

We consider a massless tracer particle moving in a random, stationary, isotropic and divergence free velocity field. We identify a class of fields, for which the limit of the laws of appropriately scaled tracer trajectory processes is…

Probability · Mathematics 2018-11-06 Tomasz Komorowski , Anna Talarczyk

We give new and explicitly computable examples of Gibbs-non-Gibbs transitions of mean-field type, using the large deviation approach introduced in [4]. These examples include Brownian motion with small variance and related diffusion…

Probability · Mathematics 2012-12-05 Frank Redig , Feijia Wang

The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including…

Probability · Mathematics 2019-11-18 Krzysztof Dȩbicki , Enkelejd Hashorva , Longmin Wang

A covariant Fokker-Planck type equation for a simple gas and an equation for the Brownian motion are derived from a relativistic kinetic theory based on the Boltzmann equation. For the simple gas the dynamic friction four-vector and the…

Statistical Mechanics · Physics 2010-11-19 Guillermo Chacón--Acosta , Gilberto M. Kremer

In this series of eight papers we present the applications of methods from wavelet analysis to polynomial approximations for a number of accelerator physics problems. In this part, according to variational approach we obtain a…

Accelerator Physics · Physics 2007-05-23 Antonina N. Fedorova , Michael G. Zeitlin

We present a qualitative diagnostic based on the continuous wavelet transform, for the detection of irregular behavior in time series of particle simulations. We apply the method to three qualitatively different gravitational 3-body…

Astrophysics · Physics 2007-05-23 Jort Gemmeke , Simon Portegies Zwart , Chael Kruip

In the relativistic and the nonrelativistic theoretical treatment of moderate and high-power laser-matter interaction, the generalized Bessel function occurs naturally when a Schr\"odinger-Volkov and Dirac-Volkov solution is expanded into…

Computational Physics · Physics 2009-11-13 Erik Lötstedt , Ulrich D. Jentschura

We consider a random two-phase process which we call a reset-return one. The particle starts its motion at the origin. The first, displacement, phase corresponds to a stochastic motion of a particle and is finished at a resetting event. The…

Statistical Mechanics · Physics 2020-05-27 Anna S. Bodrova , Igor M. Sokolov

This review paper is intended to give a useful guide for those who want to apply discrete wavelets in their practice. The notion of wavelets and their use in practical computing and various applications are briefly described, but rigorous…

High Energy Physics - Phenomenology · Physics 2025-10-20 I. M. Dremin , O. V. Ivanov , V. A. Nechitailo

We consider a weighted random walk on the backbone of an oriented percolation cluster. We determine necessary conditions on the weights for Brownian scaling limits under the annealed and the quenched law. This model is a random walk in…

Probability · Mathematics 2017-07-03 Katja Miller

The motivation of this article is to estimate multifractality classification and model selection parameters: the first-order scaling exponent $c_1$ and the second-order scaling exponent (or intermittency coefficient) $c_2$. These exponents…

Applications · Statistics 2025-03-13 Wejdene Ben Nasr , Hélène Halconruy , Stéphane Jaffard

The detail structure of the wave function is analyzed at various refinement levels using the methods of wavelet analysis. The eigenvalue problem of a model system is solved in granular Hilbert spaces, and the trajectory of the eigenstates…

Computational Physics · Physics 2009-11-13 J. Pipek , Sz. Nagy

The asymptotic behaviour, with respect to the large order, of the radii of starlikeness of two types of normalised Bessel functions is considered. We derive complete asymptotic expansions for the radii of starlikeness and provide recurrence…

Complex Variables · Mathematics 2020-09-30 Árpád Baricz , Gergő Nemes

A pathwise construction of discontinuous Brownian motions on metric graphs is given for every possible set of non-local Feller-Wentzell boundary conditions. This construction is achieved by locally decomposing the metric graphs into star…

Probability · Mathematics 2018-05-29 Florian Werner

We establish an invariance principle connecting boundary random walks on $\mathbb N$ with Feller's Brownian motions on $[0,\infty)$. A Feller's Brownian motion is a Feller process on $[0,\infty)$ whose excursions away from the boundary $0$…

Probability · Mathematics 2026-01-22 Liping Li , Zhangjie Wang

Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…

Machine Learning · Statistics 2022-04-29 Alexander Terenin