An Introduction to Kolmogorov Complexity and Its Applications. Questo articolo non è disponibile.
36 valutazioni di Goodreads
Lingua: inglese
Editore: Springer, 2013
- Brossura
- Nuovo

Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Venditore con 5 stelle
Venditore AbeBooks dal 25 marzo 2015
Non disponibile
Brossura
Condizione: Nuovo
EUR 62,11
Descrizione dell’articolo da parte del venditore
In English.
Codice articolo ria9781475726077_new
- Titolo
- An Introduction to Kolmogorov Complexity and Its Applications
- Autore
- Li, Ming; Vitanyi, Paul
- Editore
- Springer
- Anno di pubblicazione
- 2013
- Condizione
- New
- Rilegatura
- Brossura
- Lingua
- inglese
- ISBN 10
- 1475726074
- ISBN 13
- 9781475726077
- Peso dell'articolo
- 1248 grammi
Briefly, we review the basic elements of computability theory and prob ability theory that are required. Finally, in order to place the subject in the appropriate historical and conceptual context we trace the main roots of Kolmogorov complexity. This way the stage is set for Chapters 2 and 3, where we introduce the notion of optimal effective descriptions of objects. The length of such a description (or the number of bits of information in it) is its Kolmogorov complexity. We treat all aspects of the elementary mathematical theory of Kolmogorov complexity. This body of knowledge may be called algo rithmic complexity theory. The theory of Martin-Lof tests for random ness of finite objects and infinite sequences is inextricably intertwined with the theory of Kolmogorov complexity and is completely treated. We also investigate the statistical properties of finite strings with high Kolmogorov complexity. Both of these topics are eminently useful in the applications part of the book. We also investigate the recursion theoretic properties of Kolmogorov complexity (relations with Godel's incompleteness result), and the Kolmogorov complexity version of infor mation theory, which we may call "algorithmic information theory" or "absolute information theory. " The treatment of algorithmic probability theory in Chapter 4 presup poses Sections 1. 6, 1. 11. 2, and Chapter 3 (at least Sections 3. 1 through 3. 4).
"Riassunto" può appartenere a un’altra edizione di questo titolo.