信息与维度--算法视角

Jan Reimann
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引用次数: 0

摘要

本文回顾了过去三十年来分形维度与算法信息论之间关系的研究工作。它从信息论的角度阐述了无前缀科尔莫哥洛夫复杂性的基本发展,然后介绍了豪斯多夫度量和维度以及一些重要的例子。论文的主要目的是从第一原理出发,提出并发展了 "熵 = 复杂性 = 维度 "这一非正式的特征。论文的最后一部分从算法的角度介绍了对多分形度量的一些新看法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information vs Dimension -- an Algorithmic Perspective
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.
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