Filling gaps in chaotic time series

Research output: Contribution to journalArticlepeer-review


We propose a method for filling arbitrarily wide gaps in deterministic time series. Crucial to the method is the ability to apply Takens' theorem in order to reconstruct the dynamics underlying the time series. We introduce a functional to evaluate the degree of compatibility of a filling sequence of data with the reconstructed dynamics. An algorithm for finding highly compatible filling sequences with a reasonable computational effort is then discussed.

Original languageEnglish (US)
Pages (from-to)47-53
Number of pages7
JournalPhysics Letters, Section A: General, Atomic and Solid State Physics
Issue number1-3
StatePublished - Oct 10 2005


  • Chaos
  • Filling gaps
  • Time series analysis

ASJC Scopus subject areas

  • General Physics and Astronomy


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