Exploring chaotic time series and phase spaces: from dynamical systems to visual analyticsde Carvalho Pagliosa, L., 2020, [Groningen]: University of Groningen. 203 p.
Research output: Thesis › Thesis fully internal (DIV) › Academic
The analyses of time series can be enhanced by modeling it in the phase space, where its dynamics are described in a more intuitive manner. In this context, time-series observations are organized in the form of states, which are (hopefully) bounded by a well-defined structure where better insights can be inferred. However, two parameters are needed to perform such a transformation. Based on the limitations of current methods to estimate those parameters, this Ph.D. thesis investigates more robust alternatives to reconstruct phase spaces from time series.
|Qualification||Doctor of Philosophy|
|Place of Publication||[Groningen]|
|Publication status||Published - 2020|
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