MDE: MultiScale Dispersion Entropy (MDE)

In jcaude/MSEntropy: MultiScale Dispersion Entropy Calculations

Description

This function calculates the multiscale dispersion entropy (MDE) of a univariate signal x

Usage

MDE(x, m = 1, nc = 6, tau = 1, scales = 1:10)

Arguments

x	a univariate signal (vector)
m	the embedding dimension (default: 1)
nc	the number of classes (it is usually equal to a number between 3 and 9, we use 6 by default)
tau	the time lag (it is usually equal to 1)
scales	the scale factors as a vector (default 1:10)

Value

a vector of size 1 * length(scales) - the MDE of x

References

1. Azami H, Rostaghi M, Abasolo D, Escudero J (2017) "Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals". IEEE transactions on bio-medical engineering 64:2872–2879.

2. Rostaghi M, Letters HAISP, (2016) "Dispersion entropy: A measure for time-series analysis". IEEE Signal Processing Letters. vol. 23, n. 5, pp. 610-614, 2016.

Examples

data(EG_181171)
MDE(EG_181117)

jcaude/MSEntropy documentation built on May 21, 2021, 7:31 p.m.