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. ( )

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 ???
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" 2. Three inequalities of Feinstein" handler om ???
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Informationsteori som matematisk disciplin. Doob, Feinstein og Shannon. ( )