Data Compression Explained
by Matt Mahoney
Publisher: mattmahoney.net 2013
This book is for the reader who wants to understand how data compression works, or who wants to write data compression software. Prior programming ability and some math skills will be needed. This book is intended to be self contained.
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by David Feldman - College of the Atlantic
This e-book is a brief tutorial on information theory, excess entropy and statistical complexity. From the table of contents: Background in Information Theory; Entropy Density and Excess Entropy; Computational Mechanics.
by John Daugman - University of Cambridge
The aims of this course are to introduce the principles and applications of information theory. The course will study how information is measured in terms of probability and entropy, and the relationships among conditional and joint entropies; etc.
by Claude Shannon
Shannon presents results previously found nowhere else, and today many professors refer to it as the best exposition on the subject of the mathematical limits on communication. It laid the modern foundations for what is now coined Information Theory.
by Robert M. Gray - Springer
The book covers the theory of probabilistic information measures and application to coding theorems for information sources and noisy channels. This is an up-to-date treatment of traditional information theory emphasizing ergodic theory.