Title:
Information theory : a tutorial introduction / James V Stone.
Author:
Stone, James V., Dr., author.
Publication Information:
[Sheffield, United Kingdom] : Sebtel Press, 2015.
MIddletown, Delaware : [manufacturer not identified], 2015.
©2015
Call Number:
Q360 .S76 2015
Abstract:
Originally developed by Claude Shannon in the 1940s, information theory laid the foundations for the digital revolution, and is now an essential tool in telecommunications, genetics, linguistics, brain sciences, and deep space communication. In this richly illustrated book, accessible examples are used to introduce information theory in terms of everyday games like '20 questions' before more advanced topics are explored. These advanced topics include a summary of the relationship between information theory and thermodynamic entropy, and a review of applications in telecommunications and biology. Online MatLab and Python computer programs provide hands-on experience of information theory in action, and PowerPoint slides give support for teaching. Written in an informal style, with a comprehensive glossary and tutorial appendices, this text is an ideal primer for novices who wish to learn the essential principles and applications of information theory.--Publisher description.
Electronic Access:
Book website, Chapter 1, code examples, corrections http://jim-stone.staff.shef.ac.uk/BookInfoTheory/InfoTheoryBookMain.html
Edition:
First Edition.
ISBN:
9780956372857
Physical Description:
243 pages : illustrations ; 23 cm
General Note:
"A tutorial introduction book"--Page 4 of cover.
Subject Term:
Contents:
What is information? -- Entropy of discrete variables -- Source coding theorem -- Noisy channel coding theorem -- Entropy of continuous variables -- Mutual information: continuous -- Channel capacity: continuous -- Thermodynamic entropy and information -- Information as Nature's currency -- Further reading -- A. Glossary -- B. Mathematical symbols -- C. Logarithms -- D. Probability density functions -- E. Averages from distributions -- F. The rules of probability -- G. The Gaussian distribution -- H. Key equations.
Personal Author:
Subject:
