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 Keith Devlin - ESSLLI
An introductory, comparative account of three mathematical approaches to information: the classical quantitative theory of Claude Shannon, a qualitative theory developed by Fred Dretske, and a qualitative theory introduced by Barwise and Perry.
by Gregory J. Chaitin - Springer
The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical.
by Karl Petersen - AMS
The aim is to review the many facets of information, coding, and cryptography, including their uses throughout history and their mathematical underpinnings. Prerequisites included high-school mathematics and willingness to deal with unfamiliar ideas.
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.