56 lines
2.2 KiB
Matlab
56 lines
2.2 KiB
Matlab
function minmuttau = findminMutInf(miV,nsam)
|
|
% minmuttau = findminMutInf(miV,nsam)
|
|
% findminMutInf finds the lag tau of the first local minimum of mutual
|
|
% information 'miV' (given from lag 0 and up to a maximum lag 'taumax')
|
|
% and using a sliding window of length 2*nsam+1.
|
|
%========================================================================
|
|
% <findminMutInf.m>, v 1.0 2010/02/11 22:09:14 Kugiumtzis & Tsimpiris
|
|
% This is part of the MATS-Toolkit http://eeganalysis.web.auth.gr/
|
|
|
|
%========================================================================
|
|
% Copyright (C) 2010 by Dimitris Kugiumtzis and Alkiviadis Tsimpiris
|
|
% <dkugiu@gen.auth.gr>
|
|
|
|
%========================================================================
|
|
% Version: 1.0
|
|
|
|
% LICENSE:
|
|
% This program 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
|
|
% 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/>.
|
|
|
|
%=========================================================================
|
|
% Reference : D. Kugiumtzis and A. Tsimpiris, "Measures of Analysis of Time Series (MATS):
|
|
% A Matlab Toolkit for Computation of Multiple Measures on Time Series Data Bases",
|
|
% Journal of Statistical Software, in press, 2010
|
|
|
|
% Link : http://eeganalysis.web.auth.gr/
|
|
%=========================================================================
|
|
taumax = length(miV)-1;
|
|
minmuttau = NaN;
|
|
if taumax>2*nsam
|
|
i=nsam+1;
|
|
found = 0;
|
|
while i<taumax+1-nsam & found==0
|
|
winx = miV([i-nsam:i-1 i+1:i+nsam]);
|
|
check = find(miV(i) < winx);
|
|
if length(check) == length(winx)
|
|
found=1;
|
|
else
|
|
i=i+1;
|
|
end
|
|
end
|
|
if found
|
|
minmuttau = i-1;
|
|
end
|
|
end
|