Media type: E-Article Title: Coding theory Contributor: Stine, Robert A. Published: Wiley, 2009 Published in: WIREs Computational Statistics, 1 (2009) 3, Seite 261-270 Language: English DOI: 10.1002/wics.42 ISSN: 1939-5108; 1939-0068 Keywords: Statistics and Probability Origination: Footnote: Description: AbstractCoding theory is a portion of information theory concerned with the explicit representation of data as a sequence of symbols, usually a sequence of bits. The entropy of a probability distribution measures the information content of data, giving a lower bound on the number of bits necessary to encode data. Source coding also defines a measure, the divergence, of the cost of using a suboptimal representation. Channel coding describes representations that maximize the rate at which information can be communicated through a noisy medium. Important applications of coding theory include data compression, signal processing, and the comparison of statistical models. Copyright © 2009 Wiley Periodicals, Inc.This article is categorized under:Applications of Computational Statistics > Signal and Image Processing and Coding