On the relation between correlation dimension, approximate entropy and sample entropy parameters, and a fast algorithm for their calculation
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DOI: 10.1016/j.physa.2012.07.003
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Cited by:
- Ye, Xuemin & Ding, Xueliang & Zhang, Jiankun & Li, Chunxi, 2017. "Numerical simulation of pressure pulsation and transient flow field in an axial flow fan," Energy, Elsevier, vol. 129(C), pages 185-200.
- Restrepo, Juan F. & Schlotthauer, Gastón & Torres, María E., 2014. "Maximum approximate entropy and r threshold: A new approach for regularity changes detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 97-109.
- Brechtl, Jamieson & Xie, Xie & Liaw, Peter K. & Zinkle, Steven J., 2018. "Complexity modeling and analysis of chaos and other fluctuating phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 166-175.
- Vaidheeswaran, Avinash & Rowan, Steven, 2021. "Chaos and recurrence analyses of pressure signals from bubbling fluidized beds," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
- Tamara Skoric & Olivera Sarenac & Branislav Milovanovic & Nina Japundzic-Zigon & Dragana Bajic, 2017. "On Consistency of Cross-Approximate Entropy in Cardiovascular and Artificial Environments," Complexity, Hindawi, vol. 2017, pages 1-15, September.
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Keywords
Time series analysis; Sample entropy; Approximate entropy; Correlation dimension; Complexity; Medical time series; Fast numerical algorithms;All these keywords.
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