Mathematics of Information: Theory and Applications of Shannon-Wiener Information

Author:   Stefan Schäffler
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2024 ed.
Volume:   9
ISBN:  

9783662691014


Pages:   150
Publication Date:   23 July 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Mathematics of Information: Theory and Applications of Shannon-Wiener Information


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Overview

Starting with the Shannon-Wiener approach to mathematical information theory, allowing a mathematical ""measurement"" of an amount of information, the book begins by defining the terms message and information and axiomatically assigning an amount of information to a probability. The second part explores countable probability spaces, leading to the definition of Shannon entropy based on the average amount of information; three classical applications of Shannon entropy in statistical physics, mathematical statistics, and communication engineering are presented, along with an initial glimpse into the field of quantum information. The third part is dedicated to general probability spaces, focusing on the information-theoretical analysis of dynamic systems. The book builds on bachelor-level knowledge and is primarily intended for mathematicians and computer scientists, placing a strong emphasis on rigorous proofs.

Full Product Details

Author:   Stefan Schäffler
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2024 ed.
Volume:   9
ISBN:  

9783662691014


ISBN 10:   3662691019
Pages:   150
Publication Date:   23 July 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction - Symbols - List of figures - Part I Fundamentals. Message and information.- Information and chance.- Part II Countable systems. The entropy.- The maximum entropy principle.- Conditional probabilities.- Quantum information.- Part III General systems.- The entropy of partitions.- Stationary information sources.- Density functions and entropy.- Conditional expectations.- Literature.- Index.

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Author Information

Prof. Dr. Dr. Stefan Schäffler, University of the German Federal Armed Forces Munich, Faculty of Electrical Engineering and Information Technology, Chair of Mathematics and Operations Research.

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