基于dtw算法采用欧氏距离后寻找整个过程的最短匹配距离matlab代码

下面是基于DTW算法采用欧氏距离的Matlab代码：

function [dist, D] = dtw(x, y)
% x, y: two input sequences
% dist: DTW distance between x and y
% D: accumulated cost matrix

% calculate the Euclidean distance between two vectors
euclidean = @(x, y) sqrt(sum((x - y).^2));

% initialization
n = length(x);
m = length(y);
D = zeros(n+1, m+1);
D(1,:) = inf;
D(:,1) = inf;
D(1,1) = 0;

% calculate the accumulated cost matrix
for i = 2:n+1
    for j = 2:m+1
        cost = euclidean(x(i-1), y(j-1));
        D(i,j) = cost + min([D(i-1,j), D(i,j-1), D(i-1,j-1)]);
    end
end

% calculate the DTW distance
dist = D(n+1, m+1);
end

其中，输入参数`x`和`y`为两个序列，输出参数`dist`为两个序列的DTW距离，`D`为累计成本矩阵。本代码中使用了匿名函数`euclidean`来计算欧氏距离。