The Belousov-Zhabotinsky reaction is a well-known model for investigating the self-organization manifestations in nature. The chemical reaction cascade is easy to control and measure in laboratory conditions, which makes the investigation of diverse scenarios of the system behavior possible. The aim of this thesis was to evaluate the course of the reaction under the assumption of multifractality of observed chemical patterns. The approach of the information entropy theory was applied to image analysis to assess the visible changes in the reaction oscillation. Furthermore, the new characteristics - point information gain entropy and point information gain entropy density - were also introduced. These values were used to construct the state trajectory of the complex system with unique oscillation states recognition by multivariate stochastic data analysis. The reliability of the developed approach was tested on numerous experiments, including the insufficiently-studied BZ reaction wave formation under the space constriction and distortion by re-shaking effect. It has been confirmed that each of the system states has its own characteristic spectrum of information entropy. The obtained state-trajectories for the BZ reaction allows researchers to study the changing system behavior in response to variation of the initial conditions and to make a prediction about state-trajectory evolution in the imminent future. It was showed that the information entropy calculation is an effective and cheap tool for non-invasive analysis of a wide range of self-organized systems. Finally, it may be implemented also to automate laborious tasks for different cell stage recognition in medicine and biology.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:369726 |
| Date | January 2017 |
| Creators | ZHYROVA, Anna |
| Source Sets | Czech ETDs |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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