**Entropy and Information Theory**

by Robert M. Gray

**Publisher**: Springer 2008**ISBN/ASIN**: 1441979697**Number of pages**: 313

**Description**:

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.

Download or read it online for free here:

**Download link**

(1.5MB, PDF)

## Similar books

**Essential Coding Theory**

by

**Venkatesan Guruswami, Atri Rudra, Madhu Sudan**-

**University at Buffalo**

Error-correcting codes are clever ways of representing data so that one can recover the original information even if parts of it are corrupted. The basic idea is to introduce redundancy so that the original information can be recovered ...

(

**1895**views)

**Information Theory, Inference, and Learning Algorithms**

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.

(

**13136**views)

**Quantum Information 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.

(

**9605**views)

**A Mathematical Theory of Communication**

by

**Claude Shannon**

Shannon presents results previously found nowhere else, and today many professors refer to it as the best exposition on the subject of the mathematical limits on communication. It laid the modern foundations for what is now coined Information Theory.

(

**48343**views)