Derangetropy in Probability Distributions and Information Dynamics

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Ataei, Masoud, Wang, Xiaogang
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911005738532864
author Ataei, Masoud
Wang, Xiaogang
author_facet Ataei, Masoud
Wang, Xiaogang
contents We introduce derangetropy, a novel functional measure designed to characterize the dynamics of information within probability distributions. Unlike scalar measures such as Shannon entropy, derangetropy offers a functional representation that captures the dispersion of information across the entire support of a distribution. By incorporating self-referential and periodic properties, it provides deeper insights into information dynamics governed by differential equations and equilibrium states. Through combinatorial justifications and empirical analysis, we demonstrate the utility of derangetropy in depicting distribution behavior and evolution, providing a new tool for analyzing complex and hierarchical systems in information theory.
format Preprint
id arxiv_https___arxiv_org_abs_2409_15301
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Derangetropy in Probability Distributions and Information Dynamics
Ataei, Masoud
Wang, Xiaogang
Information Theory
We introduce derangetropy, a novel functional measure designed to characterize the dynamics of information within probability distributions. Unlike scalar measures such as Shannon entropy, derangetropy offers a functional representation that captures the dispersion of information across the entire support of a distribution. By incorporating self-referential and periodic properties, it provides deeper insights into information dynamics governed by differential equations and equilibrium states. Through combinatorial justifications and empirical analysis, we demonstrate the utility of derangetropy in depicting distribution behavior and evolution, providing a new tool for analyzing complex and hierarchical systems in information theory.
title Derangetropy in Probability Distributions and Information Dynamics
topic Information Theory
url https://arxiv.org/abs/2409.15301