Elements of Information Theory, Second Edition

✍ Scribed by Thomas M. Cover, Joy A. Thomas(auth.)

• Year: 2006
• Tongue: English
• Leaves: 758
• Category: Library

✦ Synopsis

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.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.Content:
Chapter 1 Introduction and Preview (pages 1–12):
Chapter 2 Entropy, Relative Entropy, and Mutual Information (pages 13–55):
Chapter 3 Asymptotic Equipartition Property (pages 57–69):
Chapter 4 Entropy Rates of a Stochastic Process (pages 71–101):
Chapter 5 Data Compression (pages 103–158):
Chapter 6 Gambling and Data Compression (pages 159–182):
Chapter 7 Channel Capacity (pages 183–241):
Chapter 8 Differential Entropy (pages 243–259):
Chapter 9 Gaussian Channel (pages 261–299):
Chapter 10 Rate Distortion Theory (pages 301–346):
Chapter 11 Information Theory and Statistics (pages 347–408):
Chapter 12 Maximum Entropy (pages 409–425):
Chapter 13 Universal Source Coding (pages 427–462):
Chapter 14 Kolmogorov Complexity (pages 463–508):
Chapter 15 Network Information Theory (pages 509–611):
Chapter 16 Information Theory and Portfolio Theory (pages 613–656):
Chapter 17 Inequalities in Information Theory (pages 657–687):