Logo

Information Theory and Statistical Physics

Small book cover: Information Theory and Statistical Physics

Information Theory and Statistical Physics
by

Publisher: arXiv
Number of pages: 176

Description:
This document consists of lecture notes for a graduate course, which focuses on the relations between Information Theory and Statistical Physics. The course is aimed at EE graduate students in the area of Communications and Information Theory, as well as to graduate students in Physics who have basic background in Information Theory. Strong emphasis is given to the analogy and parallelism between Information Theory and Statistical Physics, as well as to the insights, the analysis tools and techniques that can be borrowed from Statistical Physics and 'imported' to certain problem areas in Information Theory.

Home page url

Download or read it online for free here:
Download link
(1.2MB, PDF)

Similar books

Book cover: From Classical to Quantum Shannon TheoryFrom Classical to Quantum Shannon Theory
by - arXiv
The aim of this book is to develop 'from the ground up' many of the major developments in quantum Shannon theory. We study quantum mechanics for quantum information theory, we give important unit protocols of teleportation, super-dense coding, etc.
(11073 views)
Book cover: Logic and InformationLogic and Information
by - 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.
(12646 views)
Book cover: Lecture Notes on Network Information TheoryLecture Notes on Network Information Theory
by - arXiv
Network information theory deals with the fundamental limits on information flow in networks and optimal coding and protocols. These notes provide a broad coverage of key results, techniques, and open problems in network information theory.
(14570 views)
Book cover: Information Theory, Inference, and Learning AlgorithmsInformation Theory, Inference, and Learning Algorithms
by - 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.
(29170 views)