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 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 Robert H. Schumann - arXiv
A short review of ideas in quantum information theory. Quantum mechanics is presented together with some useful tools for quantum mechanics of open systems. The treatment is pedagogical and suitable for beginning graduates in the field.
by Alexander Shen - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, 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.