We propose a procedure to analyze experimental data which exhibit different dynamical regimes, namely, periodicity, chaoticity and quasiperiodicity by means of Recurrence Plots (RPs). We show that, based on the recurrence properties captured by RPs, we are able to characterize successfully the type of dynamics. This approach is particularly useful for detecting the existence of quasiperiodic motion in short time series. We show the capability and validity of this method by analyzing time series from fluid experiments.
Bibliographical noteA paid open access option is available for this journal.
Pre-print on arXiv and pre-print servers
Pre-print may be replaced with post-print
Post-print on authors website or institutional repository
12 month embargo for deposit in Funding Agency recommended Repositories
Must link to publisher version
Publisher copyright and source must be acknowledged
On a non-profit server
Publisher's version/PDF cannot be used
NIH Authors authors may comply with co-publisher Springers NIH Policy
Wellcome Trust authors may comply via co-publisher Springer's Open Choice
- time series