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|a Martin, Nathaniel F. G.
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|a Mathematical theory of entropy /
|c Nathaniel F.G. Martin, James W. England ; foreword by James K. Brooks.
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|a Cambridge [Cambridgeshire] ;
|a New York, NY, USA :
|b Cambridge University Press,
|c ©1984.
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300 |
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|a 1 online resource (xxi, 257 pages) :
|b illustrations
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|a online resource
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490 |
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|a Encyclopedia of mathematics and its applications ;
|v v. 12.
|a Section, Real variables
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504 |
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|a Includes bibliographical references (pages 245-251) and index.
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|a Print version record.
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|a Cover; Half Title; Series Page; Title; Copyright; Dedication; CONTENTS; Editor's Statement; Foreword; Preface; Special Symbols; CHAPTER 1 Topics from Probability Theory; 1.1 Probability Spaces; 1.2 Measurable Partitions and Lebesgue Spaces; 1.3 The Lattice of Measurable Partitions; 1.4 Random Variables; 1.5 Conditional Probability and Independence; 1.6 Conditional Expectation of Random Variables; 1.7 Stochastic Processes and Dynamical Systems; 1.8 The Ergodic Theorem and the Martingale Convergence Theorem; CHAPTER 2 Entropy and Information; 2.1 Information and Uncertainty of Events
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|a 2.2 The Information Function of an Experiment and Entropy2.3 An Example; 2.4 Conditional Information and Conditional Entropy; 2.5 Properties of Entropy and Conditional Entropy; 2.6 Entropy of Arbitrary Measurable Partitions and Limit Theorems; 2.7 Rate of Information Generation; 2.8 Entropy of Dynamical Systems; 2.9 Factor Automorphisms and Factor Systems; 2.10 Shannon's Theorem and the Equipartition Property; 2.11 Entropy as a Function of Distributions; 2.12 Examples; 2.12.1 Direct Products; 2.12.2 Skew Products; 2.12.3 Powers of Endomorphisms; 2.12 A Flows; 2.12.5 Induced Automorphisms
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|a 2.12.6 Periodic Automorphisms2.12.7 Rotations of the Circle; 2.12.8 Ergodic Automorphisms of Compact Abelian Groups; 2.12.9 Bernoulli Shifts; 2.12.10 Markov Shifts; 2.12.11 S-Automorphisms; 2.12.12 Unilateral Shifts; 2.12.13 Continued Fraction Transformations; 2.12.14 f-Transformations; 2.13 Sequence Entropy and r-Entropy; CHAPTER 3 Information Theory; 3.1 A Model of an Information System; 3.2 The Source; 3.3 Coding; 3.4 The Channel; 3.5 The Noisy Channel Coding Theorem; 3.6 Source Coding; CHAPTER 4 Ergodic Theory; 4.1 Introduction; 4.2 Unitary Operator of a System and Bernoulli Shifts
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|a 4.3 K-Systems and K-Automorphisms4.4 Spaces of Ordered Partitions, Weak Independence, and Weak Dependence; 4.5 Coding and Ornstein's Fundamental Lemma; 4.6 The Isomorphism Theorem for Bernoulli Systems; 4.7 Characterization of Bernoulli Systems; 4.8 Relative Isomorphism; 4.9 Special Flows and Equivalence Theory; CHAPTER 5 Topological Dynamics; 5.1 Introduction; 5.2 Definition and Basic Properties of Topological Entropy; 5.3 Connection between Topological and Measure Theoretic Entropy; 5.4 An Alternative Definition of Topological Entropy; CHAPTER 6 Statistical Mechanics; 6.1 Introduction
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|a 6.2 Classical Continuous Systems6.3 Classical Lattice Systems; 6.4 Gibbs States for Lattice Systems; 6.5 Equilibrium States and the Concepts of Entropy and Pressure; BIBLIOGRAPHY; Index
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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|a Entropy (Information theory)
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650 |
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|a Ergodic theory.
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650 |
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|a Statistical mechanics.
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650 |
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|a Topological dynamics.
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650 |
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|a Entropie (Théorie de l'information)
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|a Théorie ergodique.
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650 |
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|a Mécanique statistique.
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|a Dynamique topologique.
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|a MATHEMATICS
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|a Entropy (Information theory)
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|a Mathematik
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700 |
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|a England, James W.
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776 |
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|i Print version:
|a Martin, Nathaniel F.G.
|t Mathematical theory of entropy.
|d Cambridge [Cambridgeshire] ; New York, NY, USA : Cambridge University Press, ©1984
|z 0521302323
|w (DLC) 85121434
|w (OCoLC)12081912
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830 |
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|a Encyclopedia of mathematics and its applications ;
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830 |
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|a Encyclopedia of mathematics and its applications.
|p Section, Real variables.
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