Classification Problems in Ergodic Theory ( London Mathematical Society Lecture Note Series )

Publication series :London Mathematical Society Lecture Note Series

Author: William Parry;Selim Tuncel;  

Publisher: Cambridge University Press‎

Publication year: 1982

E-ISBN: 9781316922811

P-ISBN(Paperback): 9780521287944

P-ISBN(Hardback):  9780521287944

Subject: O177.99 Other

Keyword: 数学

Language: ENG

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Description

Lecturers and postgraduates in mathematics and research workers in communication engineering will find this book of use and interest. The isomorphism problem of ergodic theory has been extensively studied since Kolmogorov's introduction of entropy into the subject and especially since Ornstein's solution for Bernoulli processes. Much of this research has been in the abstract measure-theoretic setting of pure ergodic theory. The isomorphism problem of ergodic theory has been extensively studied since Kolmogorov's introduction of entropy into the subject and especially since Ornstein's solution for Bernoulli processes. Much of this research has been in the abstract measure-theoretic setting of pure ergodic theory. The isomorphism problem of ergodic theory has been extensively studied since Kolmogorov's introduction of entropy into the subject and especially since Ornstein's solution for Bernoulli processes. Much of this research has been in the abstract measure-theoretic setting of pure ergodic theory. However, there has been growing interest in isomorphisms of a more restrictive and perhaps more realistic nature which recognize and respect the state structure of processes in various ways. These notes give an account of some recent developments in this direction. A special feature is the frequent use of the information function as an invariant in a variety of special isomorphism problems. Lecturers and postgraduates in mathematics and research workers in communication engineering will find this book of use and interest. 1. Introduction; 2. The Information Cocycle; 3. Finitary Isomorphisms; 4. Block-codes; 5. Classifications of Topological Markov Chains.

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