Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and ...
Different techniques originated in information theory and tools from nonlinear systems theory have b...
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a ti...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability ...
More than ten years ago Bandt and Pompe introduced a new measure to quantify complexity in measured ...
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 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...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
Measuring complexity from non-stationary time series provides an important clue to the understanding...
Bandt and Pompe introduced Permutation Entropy as a complexity measure and has been widely used in t...
The study of permutation complexity can be envisioned as a new kind of symbolic dynamics whose basic...
Acknowledgment One of us, (SJW), wishes to acknowledge financial support from the Carnegie Trust for...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
Different techniques originated in information theory and tools from nonlinear systems theory have b...
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a ti...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability ...
More than ten years ago Bandt and Pompe introduced a new measure to quantify complexity in measured ...
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 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...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
Measuring complexity from non-stationary time series provides an important clue to the understanding...
Bandt and Pompe introduced Permutation Entropy as a complexity measure and has been widely used in t...
The study of permutation complexity can be envisioned as a new kind of symbolic dynamics whose basic...
Acknowledgment One of us, (SJW), wishes to acknowledge financial support from the Carnegie Trust for...
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring value...
Different techniques originated in information theory and tools from nonlinear systems theory have b...
Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a ti...
Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of late...