Direct computing of entropy from time series


Direct computing of entropy from time series

Kahrizsangi, Mehran Ebrahimi (2003) Direct computing of entropy from time series. Masters thesis, Concordia University.



Measure Theoretic Entropy and its important properties are studied. We introduce a method to compute entropy of a dynamical system directly from the definition. The computational approach is discussed in detail and is presented in several sections: (1) Partitioning and Scaling Data; (2) Sequencing and Compactification; (3) Probabilities and Information; (4) Entropy Estimation. Also, we apply the same method in two dimensions. A model for filtering entropy based on skew products is given, and we apply our computational results to verify this model.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Thesis (Masters)
Authors:Kahrizsangi, Mehran Ebrahimi
Pagination:viii, 69 leaves : ill., tables ; 29 cm.
Institution:Concordia University
Degree Name:Theses (M.Sc.)
Program:Mathematics and Statistics
Thesis Supervisor(s):Boyarsky, Abraham
ID Code:2347
Deposited By:Concordia University Libraries
Deposited On:27 Aug 2009 13:27
Last Modified:08 Dec 2010 10:26
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