Lecture Notes on Network Information Theory
by Abbas El Gamal, Young-Han Kim
Publisher: arXiv 2010
Number of pages: 640
Network information theory deals with the fundamental limits on information flow in networks and optimal coding techniques and protocols that achieve these limits. This set of lecture notes aims to provide a broad coverage of key results, techniques, and open problems in network information theory.
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by Peter D. Gruenwald, Paul M.B. Vitanyi - CWI
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain this quantitative approach to defining information and discuss the extent to which Kolmogorov's and Shannon's theory have a common purpose.
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 Alexander Shen - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
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.