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Mathematical foundations of information…
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Mathematical foundations of information theory (urspr publ 1953; utgåvan 1957)

av Aleksandr ÍÀkovlevich Khinchin

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1352150,926 (3.67)1
The first comprehensive introduction to information theory, this text explores the work begun by Shannon and continued by McMillan, Feinstein, and Khinchin. Its rigorous treatment addresses the entropy concept in probability theory and fundamental theorems as well as ergodic sources, the martingale concept, anticipation and memory, and other subjects. 1957 edition.… (mer)
Medlem:sumslibrary
Titel:Mathematical foundations of information theory
Författare:Aleksandr ÍÀkovlevich Khinchin
Info:New York, Dover Publications [1957] 120 p. 21 cm. [New Dover ed.]
Samlingar:Ditt bibliotek
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Mathematical Foundations of Information Theory av A. Ya. Khinchin (1953)

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This book develops Information Theory slightly further than Claude Shannon did. Although Khinchin praises Shannon for going and producing the ideas of Information Theory by himself, he acknowledges that the cases presented by Shannon were rather limited in scope to simplify the solutions.

The book as a whole is divided into two major sections; the first is called The Entropy Concept in Probability Theory and the second is called On The Fundamental Theorems of Information Theory. Both of these were originally papers printed by academic journals in the Russian Language.

The book was interesting, but I did pick out another short one, this book was only 120 pages long. ( )
  Floyd3345 | Jun 15, 2019 |
Indeholder "The Entropy Concept in Probability Theory", " 1. Entropy of Finite Schemes", " 2. The Uniqueness Theorem", " 3. Entropy of Markov chains", " 4. Fundamental Theorems", " 5. Application to Coding Theory", "On the Fundamental Theorems of Information Theory", " Introduction", " Chapter I. Elementary Inequalities", " 1. Two generalizations of Shannon's inequality", " 2. Three inequalities of Feinstein", " Chapter II. Ergodic Sources", " 3. Concept of a source. Stationarity. Entropy", " 4. Ergodic Sources", " 5. The E property. McMillan's theorem", " 6. The martingale concept. Doob's theorem", " 7. Auxiliary proposisions", " 8. Proof of McMillan's theorem", " Chapter III. Channels and the sources driving them", " 9. Concept of channel. Noise. Stationarity. Anticipation and memory", " 10. Connection of the channel to the source", " 11. The ergodic case", " Chapter IV. Feinstein's Fundamental Lemma", " 12. Formulation of the problem", " 13. Proof of the lemma", " Chapter V. Shannon's Theorems", " 14. Coding", " 15. The first Shannon theorem", " 16. The second Shannon theorem.", "Conclusion", "References".

"The Entropy Concept in Probability Theory" handler om ???
" 1. Entropy of Finite Schemes" handler om ???
" 2. The Uniqueness Theorem" handler om ???
" 3. Entropy of Markov chains" handler om ???
" 4. Fundamental Theorems" handler om ???
" 5. Application to Coding Theory" handler om ???
"On the Fundamental Theorems of Information Theory" handler om ???
" Introduction" handler om ???
" Chapter I. Elementary Inequalities" handler om ???
" 1. Two generalizations of Shannon's inequality" handler om ???
" 2. Three inequalities of Feinstein" handler om ???
" Chapter II. Ergodic Sources" handler om ???
" 3. Concept of a source. Stationarity. Entropy" handler om ???
" 4. Ergodic Sources" handler om ???
" 5. The E property. McMillan's theorem" handler om ???
" 6. The martingale concept. Doob's theorem" handler om ???
" 7. Auxiliary proposisions" handler om ???
" 8. Proof of McMillan's theorem" handler om ???
" Chapter III. Channels and the sources driving them" handler om ???
" 9. Concept of channel. Noise. Stationarity. Anticipation and memory" handler om ???
" 10. Connection of the channel to the source" handler om ???
" 11. The ergodic case" handler om ???
" Chapter IV. Feinstein's Fundamental Lemma" handler om ???
" 12. Formulation of the problem" handler om ???
" 13. Proof of the lemma" handler om ???
" Chapter V. Shannon's Theorems" handler om ???
" 14. Coding" handler om ???
" 15. The first Shannon theorem" handler om ???
" 16. The second Shannon theorem." handler om ???
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Informationsteori som matematisk disciplin. Doob, Feinstein og Shannon. ( )
  bnielsen | Jan 9, 2017 |
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Wikipedia på engelska (1)

The first comprehensive introduction to information theory, this text explores the work begun by Shannon and continued by McMillan, Feinstein, and Khinchin. Its rigorous treatment addresses the entropy concept in probability theory and fundamental theorems as well as ergodic sources, the martingale concept, anticipation and memory, and other subjects. 1957 edition.

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