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 Watrous - University of Calgary
The focus is on the mathematical theory of quantum information. We will begin with basic principles and methods for reasoning about quantum information, and then move on to a discussion of various results concerning quantum information.
by Inder Jeet Taneja - Universidade Federal de Santa Catarina
Contents: Shannon's Entropy; Information and Divergence Measures; Entropy-Type Measures; Generalized Information and Divergence Measures; M-Dimensional Divergence Measures and Their Generalizations; Unified (r,s)-Multivariate Entropies; etc.
by Abbas El Gamal, Young-Han Kim - arXiv
Network information theory deals with the fundamental limits on information flow in networks and optimal coding and protocols. These notes provide a broad coverage of key results, techniques, and open problems in network information theory.
by Gregory J. Chaitin - Springer
This book presents the core of Chaitin's theory of program-size complexity, also known as algorithmic information theory. LISP is used to present the key algorithms and to enable computer users to interact with the author's proofs.