Coarse-grained entropy rates for characterization of complex time series

DOI10.1016/0167-2789(95)00301-0zbMath0887.92002arXivcomp-gas/9512002OpenAlexW1974286061MaRDI QIDQ1913540

Milan Paluš

Publication date: 15 May 1996

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/comp-gas/9512002

zbMATH Keywords

Kolmogorov-Sinai entropytremorpharmaco-EEGcoarse-grained entropy ratescomplex time seriesphysiological signals

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Physiology (general) (92C30) Statistical aspects of information-theoretic topics (62B10) General biology and biomathematics (92B05)

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Detection of nonlinearity and chaoticity in time series using the transportation distance function ⋮ Simulation study of direct causality measures in multivariate time series ⋮ Significance testing of information theoretic functionals ⋮ Successful network inference from time-series data using mutual information rate ⋮ Unified functional network and nonlinear time series analysis for complex systems science: Thepyunicornpackage ⋮ Estimating the errors on measured entropy and mutual information ⋮ On entropy rates of dynamical systems and Gaussian processes ⋮ Space-time nature of causality ⋮ Coupling in complex systems as information transfer across time scales ⋮ Symbolic dynamics and complexity in a physiological time series ⋮ Network inference combining mutual information rate and statistical tests ⋮ The quantified histograms: Detection of the hidden unsteadiness

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