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<P>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.</P><P>THE BOOK WILL BE OF VALUE TO ADVANCED UNDERGRADUATE AND GRADUATE STUDENTS AND RESEARCHERS IN THE AREAS OF COMPUTER SCIENCE, NEUROSCIENCE, PHYSICS, AND ENGINEERING.<BR/></P>
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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.
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- VerlagSpringer
- Erscheinungsdatum2016
- ISBN 10 3319432214
- ISBN 13 9783319432212
- EinbandTapa dura
- Auflage1
- Anzahl der Seiten222
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An Introduction to Transfer Entropy : Information Flow in Complex Systems
Verlag:
Springer International Publishing
(2016)
ISBN 10: 3319432214
ISBN 13: 9783319432212
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Buchbeschreibung Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9783319432212
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