On the relation between correlation dimension, approximate entropy and sample entropy parameters, and a fast algorithm for their calculation

Sebastian Zurek, Przemyslaw Guzik, Sebastian Pawlak, Marcin Kosmider and Jaroslaw Piskorski

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 24, 6601-6610

Abstract: We explore the relation between correlation dimension, approximate entropy and sample entropy parameters, which are commonly used in nonlinear systems analysis. Using theoretical considerations we identify the points which are shared by all these complexity algorithms and show explicitly that the above parameters are intimately connected and mutually interdependent. A new geometrical interpretation of sample entropy and correlation dimension is provided and the consequences for the interpretation of sample entropy, its relative consistency and some of the algorithms for parameter selection for this quantity are discussed. To get an exact algorithmic relation between the three parameters we construct a very fast algorithm for simultaneous calculations of the above, which uses the full time series as the source of templates, rather than the usual 10%. This algorithm can be used in medical applications of complexity theory, as it can calculate all three parameters for a realistic recording of 104 points within minutes with the use of an average notebook computer.

Keywords: Time series analysis; Sample entropy; Approximate entropy; Correlation dimension; Complexity; Medical time series; Fast numerical algorithms (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:24:p:6601-6610

DOI: 10.1016/j.physa.2012.07.003

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