SampEn {FWHVA}R Documentation

Sample Entropy algorithm ~~ package title ~~

Description

A SampEn algorithm used in this study to estimate the SE is available from Physione website (http://www.physionet.org/physiotools/sampen/c/). The algorithm of SampEn has three input parameters, (1) m: the embedded dimension, (2) r: the similarity criterion, (3) n: the length of a time series. In this study, two SE features ( : m=2, r=0.15, and : m=2, r=0.2) of each epoch of EEG signals are extracted.


This algorithm excutes the HVG with $O(n)$ and also include the weighted information.
The limitation, the input length of FWHVA is less than 4098, if the input length is large than it, the stack may be overflow.

Usage

  SampEn(data, mvector, r_noise, std_flag)  

Arguments

data input data, one dimension
mvector m: the embedded dimension
r_noise r: the similarity criterion
std_flag if std_flag=='v' stdand deveratin will be used

Details

Package: FWHVA
Type: Package
Version: 1.0
Date: 2013-07-28
License: GPL (version 2 or later)

Value

sample Entropy[1..6]

Author(s)

Guohun Zhu
Maintainer: Guohun Zhu <zhuguohun@163.com> or <Guohun.Zhu@usq.edu.au>

References

Zhu, Guohun, Li, Yan, & Wen, Peng(Paul). (2013). A weighted horizontal visibility graph algorithm and its application in Epileptic EEG signal classification. submitted

and

Physione website (http://www.physionet.org/physiotools/sampen/c/)

See Also

FWHVG ~~ <FWHVA> ~~

Examples


a=c(10,8,6,4,2,1,3,5,7,9,11)
SampEn(a,3,0.2,'n')     # no std

[Package FWHVA version 1.3.0 Index]