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{ "item_title" : "An Introduction to Transfer Entropy", "item_author" : [" Terry Bossomaier", "Lionel Barnett", "Michael Harré "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/31/982/761/3319827618_b.jpg", "price_data" : { "retail_price" : "179.99", "online_price" : "179.99", "our_price" : "179.99", "club_price" : "179.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
An Introduction to Transfer Entropy|Terry Bossomaier

An Introduction to Transfer Entropy : Information Flow in Complex Systems

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Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9783319827612
  • ISBN-10: 3319827618
  • Publisher: Springer
  • Publish Date: June 2018
  • Dimensions: 9.21 x 6.14 x 0.47 inches
  • Shipping Weight: 0.7 pounds
  • Page Count: 190

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