sampenc.m

样本熵 结合样本熵和谐波小波分解

function [e,A,B]=sampenc(y,M,r);
%function [e,A,B]=sampenc(y,M,r);
%
%Input
%
%y input data
%M maximum template length
%r matching tolerance
%
%Output
%
%e sample entropy estimates for m=0,1,...,M-1
%A number of matches for m=1,...,M
%B number of matches for m=1,...,M excluding last point

n=length(y);
lastrun=zeros(1,n);
run=zeros(1,n);
A=zeros(M,1);
B=zeros(M,1);
p=zeros(M,1);
e=zeros(M,1);
for i=1:(n-1)
   nj=n-i;
   y1=y(i);
   for jj=1:nj
      j=jj+i;      
      if abs(y(j)-y1)<r
         run(jj)=lastrun(jj)+1;
         M1=min(M,run(jj));
         for m=1:M1           
            A(m)=A(m)+1;
            if j<n
               B(m)=B(m)+1;
            end            
         end
      else
         run(jj)=0;
      end      
   end
   for j=1:nj
      lastrun(j)=run(j);
   end
end
N=n*(n-1)/2;
p(1)=A(1)/N;
e(1)=-log(p(1));
for m=2:M
   p(m)=A(m)/B(m-1);
   e(m)=-log(p(m));
end