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An Introduction to Transfer Entropy

Information Flow in Complex Systems

  • Book
  • © 2016

Overview

Authors:
  1. Terry Bossomaier

    1. School of Computing and Mathematics, Charles Sturt University, Bathurst, Australia

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  2. Lionel Barnett

    1. Dept. of Informatics, University of Sussex, Brighton, United Kingdom

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  3. Michael Harré

    1. Dept. of Civil Engineering, University of Sydney, Darlington, Australia

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  4. Joseph T. Lizier

    1. Dept. of Civil Engineering, University of Sydney, Darlington, Australia

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  • 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)

  1. Front Matter

    Pages i-xxix
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  2. Introduction

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 1-10

  3. Statistical Preliminaries

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 11-32

  4. Information Theory

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 33-63

  5. Transfer Entropy

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 65-95

  6. Information Transfer in Canonical Systems

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 97-123

  7. Information Transfer in Financial Markets

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 125-138

  8. Miscellaneous Applications of Transfer Entropy

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 139-165

  9. Concluding Remarks

    • Terry Bossomaier, Lionel Barnett, Michael HarrĂ©, Joseph T. Lizier
    Pages 167-170

  10. Back Matter

    Pages 171-190
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Keywords

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

  • School of Computing and Mathematics, Charles Sturt University, Bathurst, Australia

    Terry Bossomaier

  • Dept. of Informatics, University of Sussex, Brighton, United Kingdom

    Lionel Barnett

  • Dept. of Civil Engineering, University of Sydney, Darlington, Australia

    Michael Harré, Joseph T. Lizier

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