A Short Course in Information Theory
by David J. C. MacKay
Publisher: University of Cambridge 1995
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.
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by Frederic Barbaresco, Ali Mohammad-Djafari - MDPI AG
The aim of this book is to provide an overview of current work addressing topics of research that explore the geometric structures of information and entropy. This survey will motivate readers to explore the emerging domain of Science of Information.
by David Feldman - College of the Atlantic
This e-book is a brief tutorial on information theory, excess entropy and statistical complexity. From the table of contents: Background in Information Theory; Entropy Density and Excess Entropy; Computational Mechanics.
by Robert M. Gray - Springer
The book covers the theory of probabilistic information measures and application to coding theorems for information sources and noisy channels. This is an up-to-date treatment of traditional information theory emphasizing ergodic theory.
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.