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Springer Introduction to Transfer Entropy - Information Flow Analysis

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Description

This Springer book explores transfer entropy, a metric for measuring information flow in complex systems derived from time series data. Beginning with a qualitative introduction and essential statistical foundations, the text progresses to comprehensive coverage of information theory and transfer entropy principles. The authors establish critical connections between information flow and system complexity, providing both theoretical depth and practical application. Subsequent chapters examine information transfer across canonical systems with real-world examples in neuroscience and finance, making this resource valuable for researchers and practitioners seeking to understand how information propagates through interconnected networks and dynamic systems.

Key Features

Springer publication providing rigorous academic treatment of transfer entropy methodology and applications.

Covers statistical foundations and information theory essential for understanding transfer entropy in complex systems.

Demonstrates relationships between information flow and complexity through detailed theoretical analysis.

Includes practical applications of transfer entropy in neuroscience and finance sectors.

Explores information transfer patterns in canonical systems with real-world case studies.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
24 November 2016
Listed Since
21 June 2016

Barcode

No barcode data available

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