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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Eigenvalue Estimates Using the Kolmogorov-Sinai Entropy
Entropy, 2011 The scope of this paper is twofold. First, we use the Kolmogorov-Sinai Entropy to estimate lower bounds for dominant eigenvalues of nonnegative matrices. The lower bound is better than the Rayleigh quotient.
Shih-Feng Shieh
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On the Connections of Generalized Entropies With Shannon and Kolmogorov–Sinai Entropies
Entropy, 2014 We consider the concept of generalized Kolmogorov–Sinai entropy, where instead of the Shannon entropy function, we consider an arbitrary concave function defined on the unit interval, vanishing in the origin.
Fryderyk Falniowski
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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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Maximum Entropy Production vs. Kolmogorov-Sinai Entropy in a Constrained ASEP Model
Entropy, 2014 The asymmetric simple exclusion process (ASEP) has become a paradigmatic toy-model of a non-equilibrium system, and much effort has been made in the past decades to compute exactly its statistics for given dynamical rules.
Martin Mihelich +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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