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000891671 020__ $$a9783030112981$$q(electronic book)
000891671 020__ $$a3030112985$$q(electronic book)
000891671 020__ $$z9783030112974
000891671 0248_ $$a10.1007/978-3-030-11
000891671 035__ $$aSP(OCoLC)on1106165074
000891671 035__ $$aSP(OCoLC)1106165074
000891671 040__ $$aLQU$$beng$$cLQU$$dZ5A$$dGW5XE
000891671 049__ $$aISEA
000891671 050_4 $$aQA267.7
000891671 08204 $$a511.3$$223
000891671 1001_ $$aLi, Ming,$$d1955 July 16-$$eauthor.
000891671 24513 $$aAn Introduction to Kolmogorov complexity and Its applications /$$cby Ming Li, Paul Vitányi.
000891671 250__ $$aFourth edition
000891671 264_1 $$aCham :$$bSpringer,$$c[2019]
000891671 264_4 $$c©2019
000891671 300__ $$a1 online resource (xxiii, 834 pages):$$billustrations
000891671 336__ $$atext$$btxt$$2rdacontent
000891671 337__ $$acomputer$$bc$$2rdamedia
000891671 338__ $$aonline resource$$bcr$$2rdacarrier
000891671 4901_ $$aTexts in computer science,$$x1868-095X
000891671 504__ $$aIncludes bibliographical references and index.
000891671 50500 $$g1.$$tPreliminaries --$$g2.$$tAlgorithmic Complexity --$$g3.$$tAlgorithmic Prefix Complexity --$$g4.$$tAlgorithmic Probability --$$g5.$$tInductive Reasoning --$$g6.$$tThe Incompressibility Method --$$g7.$$tResource-Bounded Complexity --$$g8.$$tPhysics, Information, and Computation.
000891671 506__ $$aAccess limited to authorized users.
000891671 520__ $$a"This must-read textbook presents an essential introduction to Kolmogorov complexity (KC), a central theory and powerful tool in information science that deals with the quantity of information in individual objects. The text covers both the fundamental concepts and the most important practical applications, supported by a wealth of didactic features. This thoroughly revised and enhanced fourth edition includes new and updated material on, amongst other topics, the Miller-Yu theorem, the Gács-Kučera theorem, the Day-Gács theorem, increasing randomness, short lists computable from an input string containing the incomputable Kolmogorov complexity of the input, the Lovász local lemma, sorting, the algorithmic full Slepian-Wolf theorem for individual strings, multiset normalized information distance and normalized web distance, and conditional universal distribution. Topics and features: Describes the mathematical theory of KC, including the theories of algorithmic complexity and algorithmic probability Presents a general theory of inductive reasoning and its applications, and reviews the utility of the incompressibility method Covers the practical application of KC in great detail, including the normalized information distance (the similarity metric) and information diameter of multisets in phylogeny, language trees, music, heterogeneous files, and clustering Discusses the many applications of resource-bounded KC, and examines different physical theories from a KC point of view Includes numerous examples that elaborate the theory, and a range of exercises of varying difficulty (with solutions) Offers explanatory asides on technical issues, and extensive historical sections Suggests structures for several one-semester courses in the preface As the definitive textbook on Kolmogorov complexity, this comprehensive and self-contained work is an invaluable resource for advanced undergraduate students, graduate students, and researchers in all fields of science."--Publisher's website.
000891671 650_0 $$aKolmogorov complexity.
000891671 7001_ $$aVitányi, P. M. B.,$$eauthor.
000891671 830_0 $$aTexts in computer science.
000891671 852__ $$bebk
000891671 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-11298-1$$zOnline Access$$91397441.1
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000891671 980__ $$aEBOOK
000891671 980__ $$aBIB
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000891671 983__ $$aOnline
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