Entropy estimation of symbol sequences
Statistical Mechanics
2017-04-24 v1 Computation and Language
Information Theory
math.IT
Data Analysis, Statistics and Probability
Machine Learning
Abstract
We discuss algorithms for estimating the Shannon entropy h of finite symbol sequences with long range correlations. In particular, we consider algorithms which estimate h from the code lengths produced by some compression algorithm. Our interest is in describing their convergence with sequence length, assuming no limits for the space and time complexities of the compression algorithms. A scaling law is proposed for extrapolation from finite sample lengths. This is applied to sequences of dynamical systems in non-trivial chaotic regimes, a 1-D cellular automaton, and to written English texts.
Cite
@article{arxiv.cond-mat/0203436,
title = {Entropy estimation of symbol sequences},
author = {Thomas Schürmann and Peter Grassberger},
journal= {arXiv preprint arXiv:cond-mat/0203436},
year = {2017}
}
Comments
14 pages, 13 figures, 2 tables