An Introduction to Transfer Entropy [recurso electrónico] : Information Flow in Complex Systems / by Terry Bossomaier, Lionel Barnett, Michael Harré, Joseph T. Lizier.

Por: Bossomaier, Terry [author.]Colaborador(es): Barnett, Lionel [author.] | Harré, Michael [author.] | Lizier, Joseph T [author.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Cham : Springer International Publishing : Imprint: Springer, 2016Descripción: XXIX, 190 p. 24 illus., 21 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319432229Tema(s): Computer science | Neurosciences | Computers | Artificial intelligence | System theory | Applied mathematics | Engineering mathematics | Computer Science | Artificial Intelligence (incl. Robotics) | Appl.Mathematics/Computational Methods of Engineering | Complex Systems | Neurosciences | Theory of Computation | Statistical Physics and Dynamical SystemsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TJ210.2-211.495Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Statistical Preliminaries -- Information Theory -- Transfer Entropy -- Information Transfer in Canonical Systems -- Information Transfer in Financial Markets -- Miscellaneous Applications of Transfer Entropy -- Concluding Remarks.
En: Springer eBooksResumen: 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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Introduction -- Statistical Preliminaries -- Information Theory -- Transfer Entropy -- Information Transfer in Canonical Systems -- Information Transfer in Financial Markets -- Miscellaneous Applications of Transfer Entropy -- Concluding Remarks.

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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