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Entropy and Information Theory
Robert M. Gray
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Description for Entropy and Information Theory
Paperback. This fully updated new edition of the classic work on information theory presents a detailed analysis of Shannon-source and channel-coding theorems, before moving on to address sources, channels, codes and the properties of information and distortion measures. Num Pages: 436 pages, biography. BIC Classification: GPJ; PBT; TJK; TTBM. Category: (G) General (US: Trade). Dimension: 235 x 155 x 23. Weight in Grams: 670.
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 in this edition:
- Expanded treatment of stationary or sliding-block codes and their relations to traditional block codes
- Expanded discussion of results from ergodic theory relevant to information theory
- Expanded treatment of B-processes -- processes formed by stationary coding memoryless sources
- New material on trading off information and distortion, including the Marton inequality
- New material on the properties of optimal ... Read more
- New material on the relationships of source coding and rate-constrained simulation or modeling of random processes
Significant material not covered in other information theory texts includes stationary/sliding-block codes, a geometric view of information theory provided by process distance measures, and general Shannon coding theorems for asymptotic mean stationary sources, which may be neither ergodic nor stationary, and d-bar continuous channels.
Show LessProduct Details
Format
Paperback
Publication date
2014
Publisher
Springer-Verlag New York Inc. United States
Number of pages
436
Condition
New
Number of Pages
409
Place of Publication
New York, United States
ISBN
9781489981325
SKU
V9781489981325
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Robert M. Gray
Robert M. Gray is the Alcatel-Lucent Technologies Professor of Communications and Networking in the School of Engineering and Professor of Electrical Engineering at Stanford University. For over four decades he has done research, taught, and published in the areas of information theory and statistical signal processing. He is a Fellow of the IEEE and the Institute for Mathematical Statistics. He ... Read more
Reviews for Entropy and Information Theory
From the book reviews: “This book is the second edition of the classic 1990 text … and inherits much of the structure and all of the virtues of the original. … this is a deep and important book, which would reward further study as the focus of a reading group or graduate course, and comes enthusiastically recommended.” (Oliver Johnson, ... Read more