Information Theory and Coding by Example

Author:   Mark Kelbert (Swansea University) ,  Yuri Suhov (University of Cambridge)
Publisher:   Cambridge University Press
ISBN:  

9781139028448


Publication Date:   05 June 2014
Format:   Undefined
Availability:   Available To Order   Availability explained
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Information Theory and Coding by Example


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Overview

This fundamental monograph introduces both the probabilistic and algebraic aspects of information theory and coding. It has evolved from the authors' years of experience teaching at the undergraduate level, including several Cambridge Maths Tripos courses. The book provides relevant background material, a wide range of worked examples and clear solutions to problems from real exam papers. It is a valuable teaching aid for undergraduate and graduate students, or for researchers and engineers who want to grasp the basic principles.

Full Product Details

Author:   Mark Kelbert (Swansea University) ,  Yuri Suhov (University of Cambridge)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press (Virtual Publishing)
ISBN:  

9781139028448


ISBN 10:   1139028448
Publication Date:   05 June 2014
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Undefined
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

'This book offers a very good overview of information theory and coding issues enriched with interesting examples selected and proposed by two experienced researchers.' Jozef Wozniak, Zentralblatt MATH This book offers a very good overview of information theory and coding issues enriched with interesting examples selected and proposed by two experienced researchers. Jozef Wozniak, Zentralblatt MATH


'This book offers a very good overview of information theory and coding issues enriched with interesting examples selected and proposed by two experienced researchers.' Jozef Wozniak, Zentralblatt MATH


Author Information

Mark Kelbert is a Reader in Statistics in the Department of Mathematics at Swansea University. For many years he has also been associated with the Moscow Institute of Information Transmission Problems and the International Institute of Earthquake Prediction Theory and Mathematical Geophysics (Moscow). Yuri Suhov is a Professor of Applied Probability in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge (Emeritus). He is also affiliated to the University of São Paolo in Brazil and to the Moscow Institute of Information Transmission Problems.

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