A student's guide to coding and information theory
By: Stefan M. Moser, Po-Ning Chen
Contributors: Chen, Po-Ning
Publisher: Cambridge University Press
Published: 2012
Place of publication: Cambridge; New York
Language: eng
Number of pages: 191
ISBN-13: 9781107015838; 9781107601963
Subjects: Coding theory; Codierungstheorie; Information theory; Informationstheorie
Notes: Includes bibliographical references and index.
Table of contents: title: 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.