Overview
- Offers a comprehensive introduction to coding theory: the reader does not need a lot of background
- Illustrates links between coding theory and statistical inference
- Presents applications to order identification in Hidden Markov chain models
Part of the book series: Springer Monographs in Mathematics (SMM)
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Table of contents (4 chapters)
Keywords
About this book
This book is accessible to anyone with a graduate level in Mathematics, and will appeal to information theoreticians and mathematical statisticians alike. Except for Chapter 4, all proofs are detailed and all tools needed to understand the text are reviewed.
Reviews
“The book represents a clear and concise description of the coding concepts … . the book can represents a good study in the fundamental of coding theory, in relations with mathematical study, the basement of developing particular models for universal coding theory.” (Nicolae Constantinescu, zbMATH 1441.94002, 2020)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Universal Coding and Order Identification by Model Selection Methods
Authors: Élisabeth Gassiat
Translated by: Anna Ben-Hamou
Series Title: Springer Monographs in Mathematics
DOI: https://doi.org/10.1007/978-3-319-96262-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-96261-0Published: 09 August 2018
Softcover ISBN: 978-3-030-07167-7Published: 28 December 2018
eBook ISBN: 978-3-319-96262-7Published: 28 July 2018
Series ISSN: 1439-7382
Series E-ISSN: 2196-9922
Edition Number: 1
Number of Pages: XV, 146
Number of Illustrations: 5 b/w illustrations
Topics: Coding and Information Theory, Statistical Theory and Methods