Analysis and identification of spatiotemporal phenomena using advanced methods of time series analysis
Abstract
The objective of the present thesis is the analysis of time series, using mainly the non-linear analysis methods, giving also emphasis to the most recently developed method of transforming time series to complex networks. The main research question that was the possibility to the identification regions presenting different dynamical behavior in the case of spatiotemporal phenomena, i.e. dynamical systems whose behavior evolves both in space and time. Our aim was to identify the dynamical state of the system, through time series analysis (system identification), to understand the dynamics of the underlying process and extract characteristic temporal/spatial characteristics of the system. The analysis was applied both to experimental and field time series. The experimental time series concern the study of various turbulent jet flow, given that in a turbulent flow there are small and large scale structures (vortices) in different temporal and spatial scales a fact that offers an excellent ...
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