Butterfly diffusion over sparse point sets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F24%3A00376566" target="_blank" >RIV/68407700:21340/24:00376566 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.physa.2024.129893" target="_blank" >https://doi.org/10.1016/j.physa.2024.129893</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.physa.2024.129893" target="_blank" >10.1016/j.physa.2024.129893</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Butterfly diffusion over sparse point sets

Popis výsledku v původním jazyce

The graph -based random walk model of fractal diffusion is limited in its use to the connected sets and does not allow for direct fractal dimension estimation based on observed data. We discuss a task of directly obtaining accurate fractal dimension estimates and propose butterfly diffusion as an alternative approach using an explicit relation between walk and fractal dimensions. The validity of the presented approach is evaluated and statistical properties of the dimension estimates are presented. Through experiments on self -similar sets, we demonstrate the effectiveness of this approach in producing unbiased dimension estimates, offering a promising tool for fractal analysis and Monte Carlo simulations. The estimate of fractal dimension can be also created from spectral dimension, but this approach is less general and less accurate.

Název v anglickém jazyce

Butterfly diffusion over sparse point sets

Popis výsledku anglicky

The graph -based random walk model of fractal diffusion is limited in its use to the connected sets and does not allow for direct fractal dimension estimation based on observed data. We discuss a task of directly obtaining accurate fractal dimension estimates and propose butterfly diffusion as an alternative approach using an explicit relation between walk and fractal dimensions. The validity of the presented approach is evaluated and statistical properties of the dimension estimates are presented. Through experiments on self -similar sets, we demonstrate the effectiveness of this approach in producing unbiased dimension estimates, offering a promising tool for fractal analysis and Monte Carlo simulations. The estimate of fractal dimension can be also created from spectral dimension, but this approach is less general and less accurate.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physica A: Statistical Mechanics and Its Applications

ISSN

0378-4371

e-ISSN

1873-2119

Svazek periodika

646

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

001259053300001

EID výsledku v databázi Scopus

2-s2.0-85196141248