Measuring complexity with zippers

Abstract

Physics concepts have often been borrowed and independently developed by other fields of science. In this perspective a significant example is that of entropy in Information Theory. The aim of this paper is to provide a short and pedagogical introduction to the use of data compression techniques for the estimate of entropy and other relevant quantities in Information Theory and Algorithmic Information Theory. We consider in particular the LZ77 algorithm as case study and discuss how a zipper can be used for information extraction.

10 pages, 3 figures

References in corpus (4)

• Language Trees and Zipping
• Entropy estimation of symbol sequences
• Data compression and learning in time sequences analysis
• Artificial Sequences and Complexity Measures

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