Entropy and Information Theory
by Robert M. Gray
Publisher: Springer 2008
Number of pages: 313
This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. This is the only up-to-date treatment of traditional information theory emphasizing ergodic theory.
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by Gregory. J. Chaitin - Cambridge University Press
The book presents the strongest possible version of Gödel's incompleteness theorem, using an information-theoretic approach based on the size of computer programs. The author tried to present the material in the most direct fashion possible.
by Mark M. Wilde - arXiv
The aim of this book is to develop 'from the ground up' many of the major developments in quantum Shannon theory. We study quantum mechanics for quantum information theory, we give important unit protocols of teleportation, super-dense coding, etc.
by David J. C. MacKay - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
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.