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Handbook Of Differential Entropy Joseph Victor Michalowicz Jonathan M Nichols

  • SKU: BELL-4747898
Handbook Of Differential Entropy Joseph Victor Michalowicz Jonathan M Nichols
$ 31.00 $ 45.00 (-31%)

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Handbook Of Differential Entropy Joseph Victor Michalowicz Jonathan M Nichols instant download after payment.

Publisher: Chapman and Hall/CRC
File Extension: PDF
File size: 8.07 MB
Pages: 244
Author: Joseph Victor Michalowicz, Jonathan M. Nichols, Frank Bucholtz
ISBN: 9781466583160, 9781466583177, 1466583169, 1466583177
Language: English
Year: 2013

Product desciption

Handbook Of Differential Entropy Joseph Victor Michalowicz Jonathan M Nichols by Joseph Victor Michalowicz, Jonathan M. Nichols, Frank Bucholtz 9781466583160, 9781466583177, 1466583169, 1466583177 instant download after payment.

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 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.

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