Ordinal Pattern Based Entropies and the Kolmogorov–Sinai Entropy: An Update [PDF]
Entropy, 2020 Different authors have shown strong relationships between ordinal pattern based entropies and the Kolmogorov−Sinai entropy, including equality of the latter one and the permutation entropy, the whole picture is however far from being complete. This
Tim Gutjahr, Karsten Keller
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Entropy Profiling: A Reduced—Parametric Measure of Kolmogorov—Sinai Entropy from Short-Term HRV Signal [PDF]
Entropy, 2020 Entropy profiling is a recently introduced approach that reduces parametric dependence in traditional Kolmogorov-Sinai (KS) entropy measurement algorithms. The choice of the threshold parameter r of vector distances in traditional entropy computations is
Chandan Karmakar +2 more
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A Multiscale Partition-Based Kolmogorov–Sinai Entropy for the Complexity Assessment of Heartbeat Dynamics [PDF]
Bioengineering, 2022 Background: Several methods have been proposed to estimate complexity in physiological time series observed at different time scales, with a particular focus on heart rate variability (HRV) series.
Andrea Scarciglia +3 more
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On Rényi Permutation Entropy [PDF]
Entropy, 2021 Among various modifications of the permutation entropy defined as the Shannon entropy of the ordinal pattern distribution underlying a system, a variant based on Rényi entropies was considered in a few papers.
Tim Gutjahr, Karsten Keller
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Statistical optimization for passive scalar transport: maximum entropy production versus maximum Kolmogorov–Sinai entropy [PDF]
Nonlinear Processes in Geophysics, 2015 We derive rigorous results on the link between the principle of maximum entropy production and the principle of maximum Kolmogorov–Sinai entropy for a Markov model of the passive scalar diffusion called the Zero Range Process.
M. Mihelich +3 more
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Stochastic Adder Circuits with Improved Entropy Output [PDF]
Entropy, 2023 Random pulse computing (RPC), the third paradigm along with digital and quantum computing, draws inspiration from biology, particularly the functioning of neurons.
Mateja Batelić, Mario Stipčević
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Trajectory classification through Freeman's curve encoding and entropic analysis. [PDF]
PLoS ONEThe classification of trajectories in two dimensions was done through an entropic analysis of their coded representation. The steps include discretising the trajectory into an 8-symbol code using the Freeman procedure.
Roxana Peña-Mendieta +5 more
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Information Dynamics of the Mother–Fetus System Using Kolmogorov–Sinai Entropy Derived from Heart Sounds: A Longitudinal Study from Early Pregnancy to Postpartum [PDF]
EntropyKolmogorov–Sinai (KS) entropy is an indicator of the chaotic behavior of entire systems from an information-theoretic viewpoint. Here, we used KS entropy values derived from the heart sounds of four fetus–mother pairs to identify the changes in fetal and
Sayuri Ishiyama +3 more
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A Benchmark for Entropy Estimators [PDF]
EntropyThis study assessed the performance of several entropy estimators for numerical time series and symbolic data on non-trivial one-dimensional dynamical systems whose Kolmogorov–Sinai entropy is known with certified accuracy: recent computer-assisted proof
Lucio M. Calcagnile +2 more
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Entanglement Dynamics and Classical Complexity [PDF]
Entropy, 2023 We study the dynamical generation of entanglement for a two-body interacting system, starting from a separable coherent state. We show analytically that in the quasiclassical regime the entanglement growth rate can be simply computed by means of the ...
Jiaozi Wang +3 more
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