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matlabÖÐÅÅÁÐìØ³ÌÐò³ö´í ÒÑÓÐ1È˲ÎÓë
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Çë½Ì£¬³ÌÐòÈçÏ£¬Çë´óÉñ°ï°ï棬 function [pe hist c] = pec(y,m,t) % Calculate the permutation entropy % Input: y: time series; % m: order of permuation entropy % t: delay time of permuation entropy, % Output: % pe: permuation entropy % hist: the histogram for the order distribution %Ref: G Ouyang, J Li, X Liu, X Li, Dynamic Characteristics of Absence EEG Recordings with Multiscale Permutation % % Entropy Analysis, Epilepsy Research, doi: 10.1016/j.eplepsyres.2012.11.003 % X Li, G Ouyang, D Richards, Predictability analysis of absence seizures with permutation entropy, Epilepsy % % Research, Vol. 77pp. 70-74, 2007 ly = length(y); permlist = perms(1:m); c(1:length(permlist))=0; for j=1:ly-t*(m-1) [a,iv]=sort(y(j:t:j+t*(m-1))); for jj=1:length(permlist) if (abs(permlist(jj, -iv))==0c(jj) = c(jj) + 1 ; end end end hist = c; c=hist(find(hist~=0)); p = c/sum(c); pe = -sum(p .* log(p)); % normalizedpe=pe/log(factorial(m)); ³ÌÐòÈçÉÏËùʾ£¬ÇëÎÊÎÒÔÚÔËÐÐʱ³öÏÖ´íÎó >> pec(a,2,6) ´íÎóʹÓà - ¾ØÕóά¶È±ØÐëÒ»Ö¡£ ³ö´í pec (line 25) if (abs(permlist(jj, -iv))==0ÕâÊÇʲôÎÊÌâÄØ£¿ |
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