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.|
|Degree Name:||Theses (M.Sc.)|
|Program:||Mathematics and Statistics|
|Thesis Supervisor(s):||Boyarsky, Abraham|
|Deposited By:||Concordia University Libraries|
|Deposited On:||27 Aug 2009 17:27|
|Last Modified:||04 Nov 2016 19:59|
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