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|a Algebraic and stochastic coding theory /
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|a Boca Raton, FL :
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|c ©2012.
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|a "Preface The purpose of writing this book is primarily to make the subject of coding theory easy for the starting senior or graduate student who possesses a thorough understanding of digital arithmetic, Boolean and modern algebra, and probability theory. In fact, any reader with these basic prerequisites will find this book interesting and useful. The contents cover the technical topics as well as material of general interest. This book explains many important technical features that have permeated the scientific and social culture of our time. The book just does not stop there. It takes the advanced readers, who have a good understanding of probability theory, stochastic analysis, and distributions, to recent theoretical developments in coding theory and shows them the limitations that the current research on the subject still imposes. For example, there still exist the following unanswered questions: What kind of overhead factor can we expect for large and small values of coding blocks? Are the different types of recent codes equivalent or do they perform differently? How do the published distributions fare in producing good codes for finite number of blocks? Is there a significant random variation in code generation for the given probability distributions? In addition, there are patent issues which deal with more efficient hardware and the expectation of the current advancement on the internet and data storage. As one can see from the above description and the table of contents, the book does not deal with any aspect of cryptography as this subject justifies a separate book, although certain rules used in this book are still useful in cryptography. What are the key benefits of this book for the readers?"
|c Provided by publisher.
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|a Includes bibliographical references and index.
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588 |
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|a Print version record.
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|a Front Cover; Dedication; Contents; Preface; Notations and Abbreviations; 1. Historical Background; 2. Digital Arithmetic; 3. Linear Codes; 4. Hamming Codes; 5. Extended Hamming Codes; 6. Bounds in Coding Theory; 7. Golay Codes; 8. Galois Fields; 9. Matrix Codes; 10. Cyclic Codes; 11. BCH Codes; 12. Reed-Muller Codes; 13. Reed-Solomon Codes; 14. Belief Propagation; 15. LDPC Codes; 16. Special LDPC Codes; 17. Discrete Distributions; 18. Erasure Codes; 19. Luby Transform Codes; 20. Raptor Codes; A. ASCII Table; B. Some Useful Groups; C. Tables in Finite Fields; D. Discrete Fourier Transform.
|
542 |
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|f Copyright © CRC Press 2012
|g 2012
|
590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
|
0 |
|a Coding theory.
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650 |
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|a Stochastic analysis.
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|a Analyse stochastique.
|
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|
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|a COMPUTERS
|x Information Theory.
|2 bisacsh
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|
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|a Coding theory
|2 fast
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|
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|a Stochastic analysis
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700 |
1 |
|
|a Kythe, Prem K.
|
776 |
0 |
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|i Print version:
|a Kythe, Dave K.
|t Algebraic and stochastic coding theory.
|d Boca Raton, FL : CRC Press, ©2012
|z 9781439881811
|w (DLC) 2011050830
|w (OCoLC)727702576
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