dtw.rar_dtw_dtw matlab_matlab_matlab计算dtw_时间序列

function [Dist,D,k,w]=dtw(r,t) % % [Dist,D,k,w]=dtw(r,t) % % 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 % r和t是测试向量和模板向量，此为待输入量 % [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); %repmat函数是为了把矩阵进行重复放置， %d就是对应点的距离矩阵 %把矢量转化为矩阵，便于求矩阵的差值d D=zeros(size(d)); D(1,1)=d(1,1); for m=2:M D(m,1)=d(m,1)+D(m-1,1); %计算垂直方向对应点的距离，相邻值加上步长 end for n=2:N D(1,n)=d(1,n)+D(1,n-1); %计算水平方向上对应点的距离，相邻值加上步长 end for m=2:M %计算对角线上的对应点的距离，此时应该找相邻3点的最小距离相加 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 % D矩阵就是累加距离D Dist=D(M,N); %D矩阵的最左下方的D(M,N)即为所求的最小距离 n=N; m=M; k=1; w=[M N]; while ((n+m)~=2) %找出最佳路径并输出 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 %values值为输出的最小值，number为最小值在所在的位置索引 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 %w为最终的最优路径 end end