Signal complexity analysis
Updated 30 Dec 2018
This package implements approximate entropy (ApEn), sample entropy (SampEn) as well as range entropies (RangeEn) A and B in MATLAB.
ApEn and SampEn have been implemented in two ways: slow and fast. The slow implementation is more intuitive and easier to follow. The idea of the fast implementation has been taken from 'sampen' function of the 'nolds' library in Python (https://pypi.org/project/nolds/#description).
RangeEn-A and RangeEn-B are based on the fast implementations of ApEn and SampEn, respectively.
You can run 'fBm_entropy_analysis' for a 'How to' example of the entropy measures on fractional Brownian motion (MATLAB's 'wfbm' function). See my github page for more examples in Python: https://github.com/omidvarnia/RangeEn.
Reference of ApEn: S. M. Pincus, “Approximate entropy as a measure of system complexity.,” Proc. Natl. Acad. Sci., vol. 88, no. 6, pp. 2297–2301, Mar. 1991.
Reference of SampEn: J. S. Richman and J. R. Moorman, “Physiological time-series analysis using approximate entropy and sample entropy,” Am. J. Physiol. Heart Circ. Physiol., vol. 278, no. 6, pp. H2039-2049, Jun. 2000.
A. Omidvarnia, M. Mesbah, M. Pedersen, and G. Jackson, “Range Entropy: A Bridge between Signal Complexity and Self-Similarity,” Entropy, vol. 20, no. 12, p. 962, Dec. 2018.
MATLAB Release Compatibility
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