Download pdf Concentration of Measure Inequalities in Information Theory, Communications and Coding
Download pdf Concentration of Measure Inequalities in Information Theory, Communications and Coding

Concentration of Measure Inequalities in Information Theory, Communications and Coding by Igal Sason

Concentration of Measure Inequalities in Information Theory, Communications and Coding
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Author: Igal Sason
Page Count: 260 pages
Published Date: 28 Apr 2015
Publisher: Now Publishers Inc
Publication Country: Hanover, United States
Language: English
ISBN: 9781601989062
File Name: Concentration.of.Measure.Inequalities.in.Information.Theory,.Communications.and.Coding.pdf
Download Link: Concentration of Measure Inequalities in Information Theory, Communications and Coding
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This second edition includes several new sections and provides a full update on all sections. This book was welcomed when it was first published as an important comprehensive treatment of the subject which is now brought fully up to date. Concentration inequalities have been the subject of exciting developments during the last two decades, and have been intensively studied and used as a powerful tool in various areas. These include convex geometry, functional analysis, statistical physics, mathematical statistics, pure and applied probability theory (e.g., concentration of measure phenomena in random graphs, random matrices, and percolation), information theory, theoretical computer science, learning theory, and dynamical systems. Concentration of Measure Inequalities in Information Theory, Communications, and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding. In addition to being a survey, this monograph also includes various new recent results derived by the authors. Concentration of Measure Inequalities in Information Theory, Communications, and Coding is essential reading for all researchers and scientists in information theory and coding.

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