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Entropy and Information Theory

This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties. New...

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Bibliographic Details
Main Author: Gray, Robert M.
Format: eBook
Language:English
Published: New York, NY Springer US 2011, 2011
Edition:2nd ed. 2011
Subjects:
Coding And Information Theory
Coding Theory
Statistics 
Probability Theory
Signal, Speech And Image Processing
Information Theory
Telecommunication
Statistics In Engineering, Physics, Computer Science, Chemistry And Earth Sciences
Communications Engineering, Networks
Signal Processing
Probabilities
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Preface
  • Introduction
  • Information Sources
  • Pair Processes: Channels, Codes, and Couplings
  • Entropy
  • The Entropy Ergodic Theorem
  • Distortion and Approximation
  • Distortion and Entropy
  • Relative Entropy
  • Information Rates
  • Distortion vs. Rate
  • Relative Entropy Rates
  • Ergodic Theorems for Densities
  • Source Coding Theorems
  • Coding for Noisy Channels
  • Bibliography
  • References
  • Index

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