Characterizing dynamical transitions by statistical complexity measures based on ordinal pattern transition networks
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Publication:3388671
DOI10.1063/5.0038876zbMath1459.37071OpenAlexW3134441847MaRDI QIDQ3388671
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Publication date: 6 May 2021
Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1063/5.0038876
Related Items (4)
Characterizing the statistical complexity of nonlinear time series via ordinal pattern transition networks ⋮ Quantifying time series complexity by multi-scale transition network approaches ⋮ A new parameter-free entropy based on fragment oscillation and its application in fault diagnosis ⋮ Multi-scale transition network approaches for nonlinear time series analysis
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