Elements of Information Theory
eBook - ePub

Elements of Information Theory

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Elements of Information Theory

About this book

The latest edition of this classic is updated with new problem sets and material
The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features:
* Chapters reorganized to improve teaching
* 200 new problems
* New material on source coding, portfolio theory, and feedback capacity
* Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

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Yes, you can access Elements of Information Theory by Thomas M. Cover,Joy A. Thomas in PDF and/or ePUB format, as well as other popular books in Computer Science & Information Technology. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title page
  3. Title page
  4. Copyright page
  5. Preface to the Second Edition
  6. Preface to the First Edition
  7. Acknowledgments for the Second Edition
  8. Acknowledgments for the First Edition
  9. Chapter 1: Introduction and Preview
  10. Chapter 2: Entropy, Relative Entropy, and Mutual Information
  11. Chapter 3: Asymptotic Equipartition Property
  12. Chapter 4: Entropy Rates of a Stochastic Process
  13. Chapter 5: Data Compression
  14. Chapter 6: Gambling and Data Compression
  15. Chapter 7: Channel Capacity
  16. Chapter 8: Differential Entropy
  17. Chapter 9: Gaussian Channel
  18. Chapter 10: Rate Distortion Theory
  19. Chapter 11: Information Theory and Statistics
  20. Chapter 12: Maximum Entropy
  21. Chapter 13: Universal Source Coding
  22. Chapter 14: Kolmogorov Complexity
  23. Chapter 15: Network Information Theory
  24. Chapter 16: Information Theory and Portfolio Theory
  25. Chapter 17: Inequalities in Information Theory
  26. Bibliography
  27. List of Symbols
  28. Index