Information Content and Entropy of Finite Patterns from a Combinatorial Perspective

Fuente: arXiv
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Autore principale: Pocze, Zsolt
Natura: Preprint
Pubblicazione: 2025
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author Pocze, Zsolt
author_facet Pocze, Zsolt
contents A unified combinatorial definition of the information content and entropy of different types of patterns, compatible with the traditional concepts of information and entropy, going beyond the limitations of Shannon information interpretable for ergodic Markov processes. We compare the information content of various finite patterns and derive general properties of information quantity from these comparisons. Using these properties, we define normalized information estimation methods based on compression algorithms and Kolmogorov complexity. From a combinatorial point of view, we redefine the concept of entropy in a way that is asymptotically compatible with traditional entropy.
format Preprint
id arxiv_https___arxiv_org_abs_2501_10824
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Information Content and Entropy of Finite Patterns from a Combinatorial Perspective
Pocze, Zsolt
Information Theory
Discrete Mathematics
A unified combinatorial definition of the information content and entropy of different types of patterns, compatible with the traditional concepts of information and entropy, going beyond the limitations of Shannon information interpretable for ergodic Markov processes. We compare the information content of various finite patterns and derive general properties of information quantity from these comparisons. Using these properties, we define normalized information estimation methods based on compression algorithms and Kolmogorov complexity. From a combinatorial point of view, we redefine the concept of entropy in a way that is asymptotically compatible with traditional entropy.
title Information Content and Entropy of Finite Patterns from a Combinatorial Perspective
topic Information Theory
Discrete Mathematics
url https://arxiv.org/abs/2501.10824