Pages that link to "Item:Q280651"
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The following pages link to Efficiently measuring complexity on the basis of real-world data (Q280651):
Displaying 14 items.
- Entropy determination based on the ordinal structure of a dynamical system (Q258245) (← links)
- Complexity-based permutation entropies: from deterministic time series to white noise (Q2060644) (← links)
- Generalized ordinal patterns allowing for ties and their applications in hydrology (Q2129611) (← links)
- Detecting regular dynamics from time series using permutations slopes (Q2198437) (← links)
- Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy (Q2205783) (← links)
- Transition-based complexity-entropy causality diagram: a novel method to characterize complex systems (Q2219597) (← links)
- Conditional entropy of ordinal patterns (Q2448781) (← links)
- Ordinal symbolic analysis and its application to biomedical recordings (Q2955727) (← links)
- Permuted Sample Entropy (Q3072384) (← links)
- A generalized permutation entropy for noisy dynamics and random processes (Q4983654) (← links)
- ordpy: A Python package for data analysis with permutation entropy and ordinal network methods (Q5000850) (← links)
- Characterizing the statistical complexity of nonlinear time series via ordinal pattern transition networks (Q6045253) (← links)
- Permutation entropy and its variants for measuring temporal dependence (Q6075175) (← links)
- Generalized ordinal patterns in discrete-valued time series: nonparametric testing for serial dependence (Q6611224) (← links)
