EN_SampEn.rar_This Is It_sample entropy_sample entropy

% EN_SampEn % % Estimates the Sample Entropy of the time series, SampEn(m,r), by referencing % code from PhysioNet. % % The publicly-available PhysioNet code, sampenc (renamed here to RN_sampenc) is % available from: % http://www.physionet.org/physiotools/sampen/matlab/1.1/sampenc.m % % cf. "Physiological time-series analysis using approximate entropy and sample % entropy", J. S. Richman and J. R. Moorman, Am. J. Physiol. Heart Circ. % Physiol., 278(6) H2039 (2000) % % This function can also calculate the SampEn of successive increments of time % series, i.e., we using an incremental differencing pre-processing, as % used in the so-called Control Entropy quantity: % % "Control Entropy: A complexity measure for nonstationary signals" % E. M. Bollt and J. Skufca, Math. Biosci. Eng., 6(1) 1 (2009) % % INPUTS: % y, the input time series % M, the embedding dimension % r, the threshold % preprocess [opt], (i) 'diff1', incremental difference preprocessing. % ------------------------------------------------------------------------------ % Copyright (C) 2013, Ben D. Fulcher <ben.d.fulcher@gmail.com>, % <http://www.benfulcher.com> % % If you use this code for your research, please cite: % B. D. Fulcher, M. A. Little, N. S. Jones., "Highly comparative time-series % analysis: the empirical structure of time series and their methods", % J. Roy. Soc. Interface 10(83) 20130048 (2010). DOI: 10.1098/rsif.2013.0048 % % This function is free software: you can redistribute it and/or modify it under % the terms of the GNU General Public License as published by the Free Software % Foundation, either version 3 of the License, or (at your option) any later % version. % % This program is distributed in the hope that it will be useful, but WITHOUT % ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS % FOR A PARTICULAR PURPOSE. See the GNU General Public License for more % details. % % You should have received a copy of the GNU General Public License along with % this program. If not, see <http://www.gnu.org/licenses/>. % ------------------------------------------------------------------------------ function out = EN_SampEn(y,M,r,preprocess) M=1; r=.1 if nargin < 4 preprocess = ''; % don't apply preprocessing end if ~isempty(preprocess) switch preprocess case 'diff1' % First do an incremental differencing of the time series % thus yielding the 'Control Entropy' y = BF_zscore(diff(y)); otherwise error('Unknown preprocessing setting ''%s''',preprocess); end end % Use the physionet code to calculate the Sample Entropy using these parameters: [e, p, ~, ~] = PN_sampenc(y,M,r); %% Give outputs for i = 1:M eval(sprintf('out.p%u = p(%u);',i,i)); eval(sprintf('out.sampen%u = e(%u);',i,i)); end out.meanchsampen = mean(diff(e)); out.meanchp = mean(diff(p));