计算两个矩阵中行的每个组合之间的距离 [英] Compute distance between each combination of rows in two matrices

问题描述

我在Matlab中遇到以下问题:

I've got the following problem in Matlab:

让我们假设我们有两个大小相同的矩阵 A 和 B ，其中每一行( m )代表了一段时间内的数据集( n ).矩阵 A 包含参考数据，矩阵 B 包含要测试的数据.现在，我想使用

Let's assume we have two matrices A and B with the same size, where each row (m) represents a dataset over time (n). Matrix A contains the reference data and Matrix B the data to be tested. I now want to compute the relative distance between each and every combination of rows in A and B using

d(m_i,m_j) = sqrt(sum((A(m_x,:)-B(m_y,:).^2))

通过for循环解决该问题会导致

Solving this via a for loop would result in

for m_x = 1:size(A,2)
    for m_y = 1:size(A,2)
        d(m_i,m_j) = sqrt(sum((A(m_i,:)-B(m_j,:).^2));
    end
end

是否有更优雅(甚至更快)的方式?

Is there a more elegant (and maybe faster) way of doing so?

推荐答案

是的.您可以使用pdist2(请参见 doc ):

Yes, there is. You can use pdist2 (see doc):

d = pdist2(A,B);

条目d(m,n)是A(m,:)和B(n,:)之间的距离.

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