Authors:
- Subject at the nexus of information theory and complex systems
- Aimed at advanced undergraduate and graduate students in computer science, neuroscience, physics, and engineering
- Includes statistical and information-theoretic background and methods of calculation
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance.
The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
Authors and Affiliations
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School of Computing and Mathematics, Charles Sturt University, Bathurst, Australia
Terry Bossomaier
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Dept. of Informatics, University of Sussex, Brighton, United Kingdom
Lionel Barnett
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Dept. of Civil Engineering, University of Sydney, Darlington, Australia
Michael Harré, Joseph T. Lizier
Bibliographic Information
Book Title: An Introduction to Transfer Entropy
Book Subtitle: Information Flow in Complex Systems
Authors: Terry Bossomaier, Lionel Barnett, Michael Harré, Joseph T. Lizier
DOI: https://doi.org/10.1007/978-3-319-43222-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-43221-2Published: 24 November 2016
Softcover ISBN: 978-3-319-82761-2Published: 28 June 2018
eBook ISBN: 978-3-319-43222-9Published: 15 November 2016
Edition Number: 1
Number of Pages: XXIX, 190
Number of Illustrations: 3 b/w illustrations, 21 illustrations in colour
Topics: Artificial Intelligence, Mathematical and Computational Engineering, Complex Systems, Neurosciences, Theory of Computation, Statistical Physics and Dynamical Systems