Overview
- Develops Kolmogorov theory in detail, and outlines a wide range of illustrative applications
- Examines major results from prominent researchers in the field
- Details the practical application of KC in the similarity metric and information diameter of multisets in phylogeny, language trees, music, heterogeneous files, and clustering
- Includes new and updated material on the Miller-Yu theorem, the Gács-Kucera theorem, the Day-Gács theorem, the Lovász local lemma, and the Slepian-Wolf theorem
- Discusses short lists computable from an input string containing the incomputable Kolmogorov complexity of the input
- Covers topics of increasing randomness, sorting, multiset normalized information distance and normalized web distance, and conditional universal distribution
- Includes supplementary material: sn.pub/extras
Part of the book series: Texts in Computer Science (TCS)
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Table of contents (8 chapters)
Keywords
About this book
This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects. The text covers both the fundamental concepts and the most important practical applications, supported by a wealth of didactic features.
This thoroughly revised and enhanced fourth edition includes new and updated material on, amongst other topics, the Miller-Yu theorem, the Gács-Kučera theorem, the Day-Gács theorem, increasing randomness, short lists computable from an input string containing the incomputable Kolmogorov complexity of the input, the Lovász local lemma, sorting, the algorithmic full Slepian-Wolf theorem for individual strings, multiset normalized information distance and normalized web distance, and conditional universal distribution.
Authors and Affiliations
About the authors
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Textbook & Academic Authors Association 2020 McGuffey Longevity Award Winner!
The judges said:
"An Introduction to Kolmogorov complexity and Its Applications has been an outstanding textbook and comprehensive reference for on information complexity for over twenty years. This new edition continues that tradition by laying a terrific foundation in the early chapters for the more advanced theories and concepts that follow. Each new theorem and corollary flows naturally and logically from what came before."
Bibliographic Information
Book Title: An Introduction to Kolmogorov Complexity and Its Applications
Authors: Ming Li, Paul Vitányi
Series Title: Texts in Computer Science
DOI: https://doi.org/10.1007/978-3-030-11298-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Ming Li and Paul Vit�nyi 2019
Hardcover ISBN: 978-3-030-11297-4Published: 26 June 2019
eBook ISBN: 978-3-030-11298-1Published: 11 June 2019
Series ISSN: 1868-0941
Series E-ISSN: 1868-095X
Edition Number: 4
Number of Pages: XXIII, 834
Number of Illustrations: 1 b/w illustrations
Topics: Applications of Mathematics, Coding and Information Theory, Theory of Computation, Algorithms, Statistical Theory and Methods, Pattern Recognition