A student's guide to coding and information theory - Info and Reading Options
By Stefan M. Moser

"A student's guide to coding and information theory" was published by Cambridge University Press in 2012 - Cambridge, it has 191 pages and the language of the book is English.
“A student's guide to coding and information theory” Metadata:
- Title: ➤ A student's guide to coding and information theory
- Author: Stefan M. Moser
- Language: English
- Number of Pages: 191
- Publisher: Cambridge University Press
- Publish Date: 2012
- Publish Location: Cambridge
“A student's guide to coding and information theory” Subjects and Themes:
- Subjects: Coding theory - Codierungstheorie - Information theory - Informationstheorie
Edition Specifications:
- Dimensions: 191 x x centimeters
- Pagination: xiii, 191 p. :
Edition Identifiers:
- The Open Library ID: OL25318269M - OL16638838W
- Online Computer Library Center (OCLC) ID: 778123334
- Library of Congress Control Number (LCCN): 2012382016
- ISBN-13: 9781107015838 - 9781107601963
- ISBN-10: 1107015839 - 1107601967
- All ISBNs: 1107015839 - 1107601967 - 9781107015838 - 9781107601963
AI-generated Review of “A student's guide to coding and information theory”:
"A student's guide to coding and information theory" Table Of Contents:
- 1- Introduction. Information theory versus coding theory -- Model and basic operations of information processing systems -- Information source -- Encoding a source alphabet -- Octal and hexadecimal codes -- Outline of the book -- References -- Error-detecting codes. Review of modular arithmetic -- Independent errors : white noise -- Single parity-check code -- The ASCII code -- Simple burst error-detecting code -- Alphabet plus number codes / weighted codes -- Trade-off between redundancy and error-detecting capability -- Further reading -- References -- Repetition and Hamming codes. Arithmetics in the binary field -- Three-times repetition code -- Hamming code -- Further reading -- References -- Data compression : efficient coding of a random message. A motivating example -- Prefix-free or instantaneous codes -- Trees and codes -- The Kraft Inequality -- Trees with probabilities -- Optimal codes : Huffman code -- Types of codes -- Some historical background -- Further reading -- References -- Entropy and Shannon's Source Coding Theorem. Motivation -- Uncertainty or entropy -- Trees revisited -- Bounds on the efficiency of codes -- Coding of an information source -- Some historical background -- Further reading -- Appendix : Uniqueness of the definition of entropy -- References -- Mutual information and channel capacity. Introduction -- The channel -- The channel relationships -- The binary symmetric channel -- System entropies -- Mutual information -- Definition of channel capacity -- Capacity of the binary symmetric channel -- Uniformly dispersive channel -- Characterization of the capacity-achieving input distribution -- Shannon's Channel Coding Theorem -- Some historical background -- Further reading -- References -- Approaching the Shannon limit by turbo coding. Information Transmission Theorem -- The Gaussian channel -- Transmission at a rate below capacity -- Transmission at a rate above capacity -- Turbo coding : an introduction -- Further reading -- Appendix : Why we assume uniform and independent data at the encoder -- Appendix : Definition of concavity -- References -- Other aspects of coding theory. Hamming code and projective geometry -- Coding and game theory -- Further reading.
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