Computational Ergodic Theory

Ergodic theory is hard to study because it is based on measure theory, which is a technically difficult subject to master for ordinary students, especially for physics majors. Many of the examples are introduced from a different perspective than in other books and theoretical ideas can be gradually...

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Bibliografski detalji
Glavni autor: Choe, Geon Ho, 19..-
Format: Livre numérique
Jezik:Anglais
Izdano: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Izdanje:1st ed. 2005.
Serija:Algorithms and Computation in Mathematics 13
Online pristup:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Bilješka: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Computational ergodic theory, Geon Ho Choe, New York, NY, Springer, 2005, 1 vol. (XIX-453 p.), Algorithms and computation in mathematics, 3-540-23121-8
• Computational Ergodic Theory, Texte imprimé, 9783540803966
• Computational ergodic theory, with 250 figures and 10 tables, Geon Ho Choe, New York, NY, Springer, 2010, 1 vol. (XIX-453 p.), Algorithms and computation in mathematics, 978-3-642-06207-0
• Computational ergodic theory, Geon Ho Choe, New York, NY, Springer, 2005, 1 vol. (XIX-453 p.), Algorithms and computation in mathematics, 3-540-23121-8
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505 1 |a Prerequisites Invariant Measures The Birkhoff Ergodic Theorem The Central Limit Theorem More on Ergodicity Homeomorphisms of the Circle Mod 2 Uniform Distribution Entropy The Lyapunov Exponent: One-Dimensional Case The Lyapunov Exponent: Multidimensional Case Stable and Unstable Manifolds Recurrence and Entropy Recurrence and Dimension Data Compression 
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520 |a Ergodic theory is hard to study because it is based on measure theory, which is a technically difficult subject to master for ordinary students, especially for physics majors. Many of the examples are introduced from a different perspective than in other books and theoretical ideas can be gradually absorbed while doing computer experiments. Theoretically less prepared students can appreciate the deep theorems by doing various simulations. The computer experiments are simple but they have close ties with theoretical implications. Even the researchers in the field can benefit by checking their conjectures, which might have been regarded as unrealistic to be programmed easily, against numerical output using some of the ideas in the book. One last remark: The last chapter explains the relation between entropy and data compression, which belongs to information theory and not to ergodic theory. It will help students to gain an understanding of the digital technology that has shaped the modern information society 
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