Arrays 使用索引kronecker乘积生成的向量构建矩阵，而不使用for循环

我可以通过舍弃for循环在Matlab中优化以下代码吗

A = [];
B = randn(4,8);
C = randn(8,4);
I = randperm(8,3);
J = randperm(8,3);
for i = 1:3
    A = [A kron(C(J(i),:)',B(:,I(i)))];
end

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是的，您可以，使用三维存储中间结果并将其转换回二维。这样你也可以避免kron本身不是最快的

Matlab R2016a或更高版本：

a = C(J,:).' .* permute(B(:,I),[3 2 1]);  %// calculation of the product to 3rd dimension
                                          %// by implicit expansion
b = permute( a, [3 1 2] );                %// permuting
out = reshape( b, [], 3 )                 %// reshape to desired form

a = bsxfun(@times , C(J,:).', permute(B(:,I),[3 2 1])); %// calculation of 
                                          %// the product to 3rd dimension(explicit)
b = permute( a, [3 1 2] );                %// permuting
out = reshape( b, [], 3 )                 %// reshape to desired form

简称：

out = reshape( permute( C(J,:).' .* permute(B(:,I),[3 2 1]), [3 1 2] ), [], 3 )

在Matlab R2016a之前：

a = C(J,:).' .* permute(B(:,I),[3 2 1]);  %// calculation of the product to 3rd dimension
                                          %// by implicit expansion
b = permute( a, [3 1 2] );                %// permuting
out = reshape( b, [], 3 )                 %// reshape to desired form

a = bsxfun(@times , C(J,:).', permute(B(:,I),[3 2 1])); %// calculation of 
                                          %// the product to 3rd dimension(explicit)
b = permute( a, [3 1 2] );                %// permuting
out = reshape( b, [], 3 )                 %// reshape to desired form

简称：

out = reshape(permute(bsxfun(@times , C(J,:).', permute(B(:,I),[3 2 1])), [3 1 2] ), [], 3 )

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下面是一个使用

kron

的矢量化版本（速度不如的答案）：