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Fully updated and revised edition of Csiszar and Korner's classic book on information theory.
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Fully updated and revised edition of Csiszar and Korner's classic book on information theory.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- 2 Revised edition
- Seitenzahl: 522
- Erscheinungstermin: 7. Januar 2016
- Englisch
- Abmessung: 244mm x 170mm x 28mm
- Gewicht: 1038g
- ISBN-13: 9781107565043
- ISBN-10: 1107565049
- Artikelnr.: 44264821
- Verlag: Cambridge University Press
- 2 Revised edition
- Seitenzahl: 522
- Erscheinungstermin: 7. Januar 2016
- Englisch
- Abmessung: 244mm x 170mm x 28mm
- Gewicht: 1038g
- ISBN-13: 9781107565043
- ISBN-10: 1107565049
- Artikelnr.: 44264821
Imre Csiszár is a Research Professor at the Rényi Institute of the Hungarian Academy of Sciences, where he has worked since 1961. He is also Professor Emeritus of the University of Technology and Economics, Budapest, a Fellow of the Institute of Electronic and Electrical Engineers (IEEE) and former President of the Hungarian Mathematical Society. He has received numerous awards, including the Shannon Award of the IEEE Information Theory Society (1996).
Part I. Information Measures in Simple Coding Problems: 1. Source coding and hypothesis testing: information measures
2. Types and typical sequences
3. Some formal properties of Shannon's information measures
4. Non-block source coding
5. Blowing up lemma: a combinatorial digression
Part II. Two-Terminal Systems: 6. The noisy channel problem
7. Rate-distortion trade-off in source coding and the source-channel transmission problem
8. Computation of channel capacity and ¿-distortion rates
9. A covering lemma: error exponent in source coding
10. A packing lemma: on the error exponent in channel coding
11. The compound channel revisited: zero-error information theory and extremal combinatorics
12. Arbitrary varying channels
Part III. Multi-Terminal Systems: 13. Separate coding of correlated source
14. Multiple-access channels
15. Entropy and image size characteristics
16. Source and channel networks
17. Information-theoretic security.
2. Types and typical sequences
3. Some formal properties of Shannon's information measures
4. Non-block source coding
5. Blowing up lemma: a combinatorial digression
Part II. Two-Terminal Systems: 6. The noisy channel problem
7. Rate-distortion trade-off in source coding and the source-channel transmission problem
8. Computation of channel capacity and ¿-distortion rates
9. A covering lemma: error exponent in source coding
10. A packing lemma: on the error exponent in channel coding
11. The compound channel revisited: zero-error information theory and extremal combinatorics
12. Arbitrary varying channels
Part III. Multi-Terminal Systems: 13. Separate coding of correlated source
14. Multiple-access channels
15. Entropy and image size characteristics
16. Source and channel networks
17. Information-theoretic security.
Part I. Information Measures in Simple Coding Problems: 1. Source coding and hypothesis testing: information measures
2. Types and typical sequences
3. Some formal properties of Shannon's information measures
4. Non-block source coding
5. Blowing up lemma: a combinatorial digression
Part II. Two-Terminal Systems: 6. The noisy channel problem
7. Rate-distortion trade-off in source coding and the source-channel transmission problem
8. Computation of channel capacity and ¿-distortion rates
9. A covering lemma: error exponent in source coding
10. A packing lemma: on the error exponent in channel coding
11. The compound channel revisited: zero-error information theory and extremal combinatorics
12. Arbitrary varying channels
Part III. Multi-Terminal Systems: 13. Separate coding of correlated source
14. Multiple-access channels
15. Entropy and image size characteristics
16. Source and channel networks
17. Information-theoretic security.
2. Types and typical sequences
3. Some formal properties of Shannon's information measures
4. Non-block source coding
5. Blowing up lemma: a combinatorial digression
Part II. Two-Terminal Systems: 6. The noisy channel problem
7. Rate-distortion trade-off in source coding and the source-channel transmission problem
8. Computation of channel capacity and ¿-distortion rates
9. A covering lemma: error exponent in source coding
10. A packing lemma: on the error exponent in channel coding
11. The compound channel revisited: zero-error information theory and extremal combinatorics
12. Arbitrary varying channels
Part III. Multi-Terminal Systems: 13. Separate coding of correlated source
14. Multiple-access channels
15. Entropy and image size characteristics
16. Source and channel networks
17. Information-theoretic security.