TOCSY - Toolboxes for Complex Systems: PETROPY. Permutation entropy provides a simple and robust method to estimate complexity of time series, taking the temporal order of the values into account. Furthermore, permutation entropy can be used to determine embedding parameters or identify couplings between time series. For further instructions please consider the reference given below.
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References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Ciarrocchi, Nicolás; Quiróz, Nicolás; Traversaro, Francisco; Roman, Eduardo San; Risk, Marcelo; Goldemberg, Fernando; Redelico, Francisco O.: The complexity of intracranial pressure as an indicator of cerebral autoregulation (2019)
- Traversaro, Francisco; O. Redelico, Francisco: Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy (2018)
- Traversaro, Francisco; Redelico, Francisco O.; Risk, Marcelo R.; Frery, Alejandro C.; Rosso, Osvaldo A.: Bandt-Pompe symbolization dynamics for time series with tied values: a data-driven approach (2018)
- Zunino, Luciano; Kulp, Christopher W.: Detecting nonlinearity in short and noisy time series using the permutation entropy (2017)
- Chen, Yang; Zhao, Dong-Jie; Wang, Zi-Yang; Wang, Zhong-Yi; Tang, Guiliang; Huang, Lan: Plant electrical signal classification based on waveform similarity (2016)
- Kulp, C. W.; Zunino, L.: Discriminating chaotic and stochastic dynamics through the permutation spectrum test (2014)