Acknowledgment One of us, (SJW), wishes to acknowledge financial support from the Carnegie Trust for his summer project.Peer reviewedPostprin
More than ten years ago Bandt and Pompe introduced a new measure to quantify complexity in measured ...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...
L.R. and A.P. contributed equally to this work. Funding: This research received no external funding....
Permutation entropy measures the complexity of a deterministic time series via a data symbolic quant...
This is a paper in the intersection of time series analysis and complexity theory that presents new...
This is a paper in the intersection of time series analysis and complexity theory that presents new ...
This is a review of group entropy and its application to permutation complexity. Specifically, we re...
This is a review of group entropy and its application to permutation complexity. Specifically, we re...
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability ...
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a ti...
Multiscale entropy (MSE) has become a prevailing method to quantify the complexity of systems. Unfor...
Bandt and Pompe introduced Permutation Entropy as a complexity measure and has been widely used in t...
Multiscale permutation entropy (MPE) has recently been proposed to evaluate complexity of time serie...
Measuring complexity from non-stationary time series provides an important clue to the understanding...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
More than ten years ago Bandt and Pompe introduced a new measure to quantify complexity in measured ...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...
L.R. and A.P. contributed equally to this work. Funding: This research received no external funding....
Permutation entropy measures the complexity of a deterministic time series via a data symbolic quant...
This is a paper in the intersection of time series analysis and complexity theory that presents new...
This is a paper in the intersection of time series analysis and complexity theory that presents new ...
This is a review of group entropy and its application to permutation complexity. Specifically, we re...
This is a review of group entropy and its application to permutation complexity. Specifically, we re...
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability ...
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a ti...
Multiscale entropy (MSE) has become a prevailing method to quantify the complexity of systems. Unfor...
Bandt and Pompe introduced Permutation Entropy as a complexity measure and has been widely used in t...
Multiscale permutation entropy (MPE) has recently been proposed to evaluate complexity of time serie...
Measuring complexity from non-stationary time series provides an important clue to the understanding...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
More than ten years ago Bandt and Pompe introduced a new measure to quantify complexity in measured ...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...
L.R. and A.P. contributed equally to this work. Funding: This research received no external funding....
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