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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.

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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:M.Sc.
Thesis Supervisor(s):Boyarsky, Abraham
ID Code:2347
Deposited By: Concordia University Library
Deposited On:27 Aug 2009 17:27
Last Modified:18 Jan 2018 17:19
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