A Short Course in Information Theory
by David J. C. MacKay
Publisher: University of Cambridge 1995
Description:
Is it possible to communicate reliably from one point to another if we only have a noisy communication channel? How can the information content of a random variable be measured? This course will discuss the remarkable theorems of Claude Shannon, starting from the source coding theorem, which motivates the entropy as the measure of information, and culminating in the noisy channel coding theorem. Along the way we will study simple examples of codes for data compression and error correction.
Download or read it online for free here:
Download link
(multiple PDF,PS files)
Similar books
Error-Correction Coding and Decodingby Martin Tomlinson, et al. - Springer
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies.
(1128 views)
Information Theory and Codingby 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.
(12873 views)
Information Theory, Inference, and Learning Algorithmsby 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.
(17089 views)
Quantum Information Theoryby Renato Renner - ETH Zurich
Processing of information is necessarily a physical process. It is not surprising that physics and the theory of information are inherently connected. Quantum information theory is a research area whose goal is to explore this connection.
(6719 views)