An Introduction to Transfer Entropy: Information Flow in Complex Systems
Autor Terry Bossomaier, Lionel Barnett, Michael Harré, Joseph T. Lizieren Limba Engleză Hardback – 24 noi 2016
The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
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Specificații
ISBN-13: 9783319432212
ISBN-10: 3319432214
Pagini: 208
Ilustrații: XXIX, 190 p. 24 illus., 21 illus. in color.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.49 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3319432214
Pagini: 208
Ilustrații: XXIX, 190 p. 24 illus., 21 illus. in color.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.49 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
Introduction.- Statistical Preliminaries.- Information Theory.- Transfer Entropy.- Information Transfer in Canonical Systems.- Information Transfer in Financial Markets.- Miscellaneous Applications of Transfer Entropy.- Concluding Remarks.
Textul de pe ultima copertă
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.
The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.
Caracteristici
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