Date of Award

10-5-2017

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Mathematics and Statistics

First Advisor

Caron, Richard

Second Advisor

Gras, Robin

Keywords

chaos, deterministic, Higuchi, optimization, Poincaré, stochastic

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

This thesis is concerned with chaos theory and the analysis of time series using the Poincar e and Higuchi (P&H) method. The P&H method has been shown to qualitatively di erentiate between deterministic and stochastic time series. This thesis proposes that the P&H method can be extended to also quantitatively di erentiate between deterministic and stochastic time series. This extension of the P&H method was tested on twelve time series: six produced by deterministic chaotic systems and six produced by stochastic processes. Results show that, even with noise, the P&H method can quantitatively di erentiate between these two sets of time series. This thesis also studies the problem of optimizing the location of the Poincar e section used in the P&H method. Proposed optimization methods were tested on the same twelve time series. Of the methods tested, the most e ective Poincar e sections were found by a local search method.

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