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這是下載的用MATLAB實(shí)現(xiàn)的DTW算法，問(wèn)題是怎么用這個(gè)算法簡(jiǎn)單測(cè)試一下，例如兩個(gè)序列(3，5，6，7，7，1)(3,6,6,7,8,1,1)用這個(gè)算法計(jì)算這兩個(gè)序列的相似性？哪個(gè)大神幫幫忙，本人菜鳥(niǎo)一枚

function [Dist,D,k,w,rw,tw]=dtw(r,t)

%

% [Dist,D,k,w,rw,tw]=dtw(r,t,pflag)

%

% Dynamic Time Warping Algorithm 動(dòng)態(tài)時(shí)間規(guī)整算法

% Dist is unnormalized distance between t and r Dist是t和r之間的非標(biāo)準(zhǔn)化距離

% D is the accumulated distance matrix D是累積的距離矩陣

% k is the normalizing factor k是正態(tài)因子

% w is the optimal path w是最佳路徑

% t is the vector you are testing against t是你要測(cè)試的矢量

% r is the vector you are testing r是你正在測(cè)試的矢量

% rw is the warped r vector rw是扭曲的r矢量

% tw is the warped t vector tw是扭曲的t矢量

% pflag plot flag: 1 (yes), 0(no) pflag圖標(biāo)記:1(yes)，0(no)

%

% Version comments: 文本的評(píng)論:

% rw, tw and pflag added by Pau Mic

[row,M]=size(r); if (row > M) M=row; r=r'; end;

[row,N]=size(t); if (row > N) N=row; t=t'; end;

d=sqrt((repmat(r',1,N)-repmat(t,M,1)).^2); %this makes clear the above instruction Thanks Pau Mic

D=zeros(size(d));

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

for m=2:M

D(m,1)=d(m,1)+D(m-1,1);

end

for n=2:N

D(1,n)=d(1,n)+D(1,n-1);

end

for m=2:M

for n=2:N

D(m,n)=d(m,n)+min(D(m-1,n),min(D(m-1,n-1),D(m,n-1))); % this double MIn construction improves in 10-fold the Speed-up. Thanks Sven Mensing

end

end

Dist=D(M,N);

n=N;

m=M;

k=1;

w=[M N];

while ((n+m)~=2)

if (n-1)==0

m=m-1;

elseif (m-1)==0

n=n-1;

else

[values,number]=min([D(m-1,n),D(m,n-1),D(m-1,n-1)]);

switch number

case 1

m=m-1;

case 2

n=n-1;

case 3

m=m-1;

n=n-1;

end

end

k=k+1;

w=[m n; w]; % this replace the above sentence. Thanks Pau Mic

end

% warped waves

rw=r(w(:,1));

tw=t(w(:,2));

end

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