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The Theory of Information and Coding (Encyclopedia of Mathematics and its Applications No. 86)
 
 
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The Theory of Information and Coding (Encyclopedia of Mathematics and its Applications No. 86) [Hardcover]

Robert J. McEliece (Author)
4.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

May 6, 2002 0521000955 978-0521000956 2nd
This revised edition of McEliece's classic is a self-contained introduction to all basic results in the theory of information and coding. This theory was developed to deal with the fundamental problem of communication, that of reproducing at one point, either exactly or approximately, a message selected at another point. There is a short and elementary overview introducing the reader to the concept of coding. Following the main results, the channel and source coding theorems is a study of specific coding schemes which can be used for channel and source coding. This volume can be used either for self-study, or for a graduate/undergraduate level course at university. It includes dozens of worked examples and several hundred problems for solution.

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Editorial Reviews

Review

'... [An] outstanding book ...'. Albert A. Mullin, Zentralblatt MATH

Book Description

This is a revised edition of McEliece's classic. This volume is a self-contained introduction to all basic results in the theory of information and coding (invented by Claude Shannon in 1948). This theory was developed to deal with the fundamental problem of communication, that of reproducing at one point, either exactly or approximately, a message selected at another point. This volume can be used either for self-study, or for a graduate/undergradute level course at university. The text includes dozens of worked examples and several hundred problems for solution.

Product Details

  • Hardcover: 400 pages
  • Publisher: Cambridge University Press; 2nd edition (May 6, 2002)
  • Language: English
  • ISBN-10: 0521000955
  • ISBN-13: 978-0521000956
  • Product Dimensions: 9.1 x 6.1 x 1.1 inches
  • Shipping Weight: 1.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,292,203 in Books (See Top 100 in Books)

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6 of 7 people found the following review helpful:
4.0 out of 5 stars Updating a classic text, May 9, 2004
This review is from: The Theory of Information and Coding (Encyclopedia of Mathematics and its Applications No. 86) (Hardcover)
An excellent update of a classic text. This book, in just this one volume, gives you an incisive description of information theory. It assumes that you have no prior experience in this field. It develops the theory from the first principles of Claude Shannon, and rapidly shows you his major results.

If you are a student, a valuable and essential part of the book are the several hundred questions. You really need to tackle as many of these as you can. By doing so, you can substantially deepen your understanding of the subject. The problem sets are probably also another reason why this book has become a common text in Information Theory classes.

The first edition of this book (and now hopefully this edition!) has been compared by some to Richard Feynman's Lectures on Physics, as a standard and authoritative book in its field.

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Inside This Book (learn more)
First Sentence:
Suppose X is a discrete random variable, that is, one whose range R = {x1, x2, . . .} is finite or countable. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
binary symmetric source, actual transmitted codeword, lower shift register, burst descriptions, upper shift register, destination alphabet, decoder error probability, codeword components, source coding theorem, right cyclic shift, decoding cycle, channel input symbols, path enumerator, cyclic code, corrected codeword, channel coding theorem, erasure symbol, binary linear code, channel transition probabilities, weight enumerator, sequential decoding algorithm, discrete memoryless source, locator polynomial, discrete quantizations, test channel
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Prove Lemma, Definition Let, Generalize Theorem, Using Table
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