Information vs. Dimension: An algorithmic perspective

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Abstract

This paper surveys work on the relation between fractal dimensions and algorithmic information theory over the past thirty years. It covers the basic development of prefix-free Kolmogorov complexity from an information theoretic point of view, before introducing Hausdorff measures and dimension along with some important examples. The main goal of the paper is to motivate and develop the informal identity “entropy = complexity = dimension” from first principles. The last section of the paper presents some new observations on multifractal measures from an algorithmic viewpoint.

Original languageEnglish (US)
Title of host publicationStructure And Randomness In Computability And Set Theory
PublisherWorld Scientific Publishing Co.
Pages111-151
Number of pages41
ISBN (Electronic)9789813228238
DOIs
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Computer Science(all)

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