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 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 Raymond Yeung, S-Y Li, N Cai - Now Publishers Inc
A tutorial on the basics of the theory of network coding. It presents network coding for the transmission from a single source node, and deals with the problem under the more general circumstances when there are multiple source nodes.
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 ...
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.