
Published online:
01 September 2009
Published in print:
22 January 2009
Online ISBN:
9780191718755
Print ISBN:
9780198570837
Contents
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1.1 Random variables 1.1 Random variables
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1.2 Entropy 1.2 Entropy
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1.3 Sequences of random variables and their entropy rate 1.3 Sequences of random variables and their entropy rate
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1.4 Correlated variables and mutual information 1.4 Correlated variables and mutual information
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1.5 Data compression 1.5 Data compression
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1.5.1 Codewords 1.5.1 Codewords
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1.5.2 Optimal compression and entropy 1.5.2 Optimal compression and entropy
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1.6 Data transmission 1.6 Data transmission
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1.6.1 Communication channels 1.6.1 Communication channels
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1.6.2 Error-correcting codes 1.6.2 Error-correcting codes
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1.6.3 The channel coding theorem 1.6.3 The channel coding theorem
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Notes Notes
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Chapter
1 Introduction to information theory
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Pages
3–22
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Published:January 2009
Cite
Mézard, Marc, and Andrea Montanari, 'Introduction to information theory', Information, Physics, and Computation, Oxford Graduate Texts (Oxford , 2009; online edn, Oxford Academic, 1 Sept. 2009), https://doi.org/10.1093/acprof:oso/9780198570837.003.0001, accessed 29 Apr. 2025.
Abstract
This chapter introduces some of the basic concepts of information theory, as well as the definitions and notations of probability theory that are used throughout the book. It defines the fundamental notions of entropy, relative entropy, and mutual information. It also presents the main questions of information theory: data compression and data transmission. Finally, it offers a brief introduction to error correcting codes and Shannon's theory.
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