Kahrizsangi, Mehran Ebrahimi (2003) Direct computing of entropy from time series. Masters thesis, Concordia University.
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Abstract
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 |
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Item Type: | Thesis (Masters) |
Authors: | Kahrizsangi, Mehran Ebrahimi |
Pagination: | viii, 69 leaves : ill., tables ; 29 cm. |
Institution: | Concordia University |
Degree Name: | M.Sc. |
Program: | Mathematics |
Date: | 2003 |
Thesis Supervisor(s): | Boyarsky, Abraham |
Identification Number: | QC 318 E57K34 2003 |
ID Code: | 2347 |
Deposited By: | Concordia University Library |
Deposited On: | 27 Aug 2009 17:27 |
Last Modified: | 13 Jul 2020 19:52 |
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