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Dynamic Time Warping

Dynamic Time Warping

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08 Dec 2004 (Updated )

Dynamic time warping program. Calculates the similarity between 2 vectors.

[Dist,D,k,w]=dtw(t,r)
function [Dist,D,k,w]=dtw(t,r)
%Dynamic Time Warping Algorithm
%Dist is unnormalized distance between t and r
%D is the accumulated distance matrix
%k is the normalizing factor
%w is the optimal path
%t is the vector you are testing against
%r is the vector you are testing
[rows,N]=size(t);
[rows,M]=size(r);
%for n=1:N
%    for m=1:M
%        d(n,m)=(t(n)-r(m))^2;
%    end
%end
d=(repmat(t(:),1,M)-repmat(r(:)',N,1)).^2; %this replaces the nested for loops from above Thanks Georg Schmitz 

D=zeros(size(d));
D(1,1)=d(1,1);

for n=2:N
    D(n,1)=d(n,1)+D(n-1,1);
end
for m=2:M
    D(1,m)=d(1,m)+D(1,m-1);
end
for n=2:N
    for m=2:M
        D(n,m)=d(n,m)+min([D(n-1,m),D(n-1,m-1),D(n,m-1)]);
    end
end

Dist=D(N,M);
n=N;
m=M;
k=1;
w=[];
w(1,:)=[N,M];
while ((n+m)~=2)
    if (n-1)==0
        m=m-1;
    elseif (m-1)==0
        n=n-1;
    else 
      [values,number]=min([D(n-1,m),D(n,m-1),D(n-1,m-1)]);
      switch number
      case 1
        n=n-1;
      case 2
        m=m-1;
      case 3
        n=n-1;
        m=m-1;
      end
  end
    k=k+1;
    w=cat(1,w,[n,m]);
end

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