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Course, academic year 2023/2024
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Entropy in probability dynamical systems - NSTP060
Title: Entropie v pravděpodobnostních dynamických systémech
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2014
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: cancelled
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: Mgr. Michal Kupsa
Class: DS, pravděpodobnost a matematická statistika
Classification: Mathematics > Probability and Statistics
Interchangeability : NMTP569
Annotation -
Last update: T_KPMS (03.05.2011)
The basic elements of ergodic theory are presented. We mainly focus on entropy and recurrence. Tight relationship between ergodic theory and the theory of finite-states stationary processes will be presented.
Aim of the course -
Last update: T_KPMS (03.05.2011)

To present the broadly used notion of entropy in the frame of the ergodic theory.

Literature - Czech
Last update: T_KPMS (03.05.2011)

K. Petersen: Ergodic Theory, Cambridge Univ. Press, 1983

P. Shields: The Ergodic Theory of Discrete Sample Path, Graduate Studies in Mathematics, AMS, 1996

Teaching methods -
Last update: T_KPMS (03.05.2011)

Lecture.

Syllabus -
Last update: T_KPMS (03.05.2011)

1. Probability (measure-theoretical) dynamical systems, finite-states stationary processes - definitions, examples, ergodicity, isomorfismus of probability dynamical systems, factorization

2. Entropy of the process, entropy of the system, strictly positive entropy - Kolmogorov property

3. Kolmogorov-Sinai theorem on generators, Shannon-McMillan-Breimann theorem

4. Recurrence, Ornstein-Weiss theorem, Lempel-Ziv algorithm for data compression

 
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