Publication

Exploring chaotic time series and phase spaces: from dynamical systems to visual analytics

de Carvalho Pagliosa, L., 2020, [Groningen]: University of Groningen. 203 p.

Research output: ThesisThesis fully internal (DIV)Academic

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Documents

  • Title and contents

    Final publisher's version, 280 KB, PDF document

  • Chapter 1

    Final publisher's version, 472 KB, PDF document

  • Chapter 2

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  • Chapter 3

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  • Chapter 4

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  • Chapter 5

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  • Chapter 6

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  • Chapter 7

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  • Chapter 8

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  • Chapter 9

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  • Chapter 10

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  • Bibliography

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  • Acknowledgements

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  • Complete thesis

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  • Propositions

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DOI

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.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
Supervisors/Advisors
  • de Mello, R.F., Supervisor, External person
  • Telea, Alexandru, Supervisor
  • Biehl, M. , Assessment committee
  • Karastoyanova, Dimka, Assessment committee
  • Ferreira, C.H.G., Assessment committee, External person
  • Rodrigues, F.A., Assessment committee, External person
Award date16-Mar-2020
Place of Publication[Groningen]
Publisher
Print ISBNs978-94-034-2245-9
Electronic ISBNs978-94-034-2244-2
Publication statusPublished - 2020

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