Handbook of differential entropy

Unlike related books, this handbook brings together background material, derivations, and applications of differential entropy. The book first reviews probability theory as it enables an understanding of the core building block of entropy. The authors then carefully explain both discrete and differe...

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Bibliographic Details
Main Authors Bucholtz, Frank, Michalowicz, Joseph Victor, Nichols, Jonathan Michael
Format eBook Book
LanguageEnglish
Published Boca Raton, Fla CRC Press, Taylor & Francis Group 2014
CRC Press LLC
Chapman & Hall
CRC Press
Edition1
Subjects
Entropy
Mathematical physics
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Abstract Unlike related books, this handbook brings together background material, derivations, and applications of differential entropy. The book first reviews probability theory as it enables an understanding of the core building block of entropy. The authors then carefully explain both discrete and differential entropy. They present detailed derivations of differential entropy for numerous probability models, discuss challenges with interpreting and deriving differential entropy, and show how differential entropy varies as a function of the model variance. They also explore the application of differential entropy in several areas.
AbstractList One of the main issues in communications theory is measuring the ultimate data compression possible using the concept of entropy. While differential entropy may seem to be a simple extension of the discrete case, it is a more complex measure that often requires a more careful treatment. Handbook of Differential Entropyprovides a comprehensive introduction to the subject for researchers and students in information theory. Unlike related books, this one brings together background material, derivations, and applications of differential entropy. The handbook first reviews probability theory as it enables an understanding of the core building block of entropy. The authors then carefully explain the concept of entropy, introducing both discrete and differential entropy. They present detailed derivations of differential entropy for numerous probability models and discuss challenges with interpreting and deriving differential entropy. They also show how differential entropy varies as a function of the model variance. Focusing on the application of differential entropy in several areas, the book describes common estimators of parametric and nonparametric differential entropy as well as properties of the estimators. It then uses the estimated differential entropy to estimate radar pulse delays when the corrupting noise source is non-Gaussian and to develop measures of coupling between dynamical system components.
Unlike related books, this handbook brings together background material, derivations, and applications of differential entropy. The book first reviews probability theory as it enables an understanding of the core building block of entropy. The authors then carefully explain both discrete and differential entropy. They present detailed derivations of differential entropy for numerous probability models, discuss challenges with interpreting and deriving differential entropy, and show how differential entropy varies as a function of the model variance. They also explore the application of differential entropy in several areas.
One of the main issues in communications theory is measuring the ultimate data compression possible using the concept of entropy. While differential entropy may seem to be a simple extension of the discrete case, it is a more complex measure that often requires a more careful treatment.Handbook of Differential Entropy provides a comprehensive intro.
Author Michalowicz, Joseph Victor
Nichols, Jonathan Michael
Bucholtz, Frank
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Snippet Unlike related books, this handbook brings together background material, derivations, and applications of differential entropy. The book first reviews...
One of the main issues in communications theory is measuring the ultimate data compression possible using the concept of entropy. While differential entropy...
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TableOfContents Front Cover -- Contents -- List of Figures -- List of Tables -- Preface -- Chapter 1 - Probability in Brief -- Chapter 2 - The Concept of Entropy -- Chapter 3 - Entropy for Discrete Probability Distributions -- Chapter 4 - Differential Entropies for Probability Distributions -- Chapter 5 - Differential Entropy as a Function of Variance -- Chapter 6 - Applications of Differential Entropy -- Chapter 7 - Appendices -- Bibliography -- Back Cover
Title Handbook of differential entropy
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