bsxfun实现中的最小化解决方案.优化任务 [英] bsxfun implementation in solving a min. optimization task

问题描述

我真的需要这个帮助.

I really need help with this one.

我必须使用矩阵L1和L2，它们的大小均为(500x3).

I have to matrices L1 and L2, both are (500x3) of size.

首先，我计算L1的每个列中每个元素与L2的差值，如下所示:

First of all, I compute the difference of every element of each column of L1 from L2 as follows:

lib1 = bsxfun(@minus, L1(:,1)',L2(:,1));
lib1=lib1(:);
lib2 = bsxfun(@minus, L1(:,2)',L2(:,2));
lib2=lib2(:);
lib3 = bsxfun(@minus, L1(:,3)',L2(:,3));
lib3=lib3(:);
LBR = [lib1 lib2 lib3];

结果是此矩阵LBR.然后我有一个min问题要解决:

The result is this matrix LBR. Then I have a min-problem to solve:

[d,p] = min((LBR(:,1) - var1).^2 + (LBR(:,2) - var2).^2 + (LBR(:,3) - var3).^2);

哪个返回点p满足该min问题的位置.最后，我可以回到矩阵L1和L2来找到满足该min问题的值的索引位置.我这样做如下:

Which returns the point p where this min-problem is fulfied. Finally I can go back to my matrices L1 and L2 to find the index-positions of the values which satisfy this min-problem. I done this as follows:

[minindex_alongL2, minindex_alongL1] = ind2sub(size(L1),p);

这可以.但是我现在需要的是:

This is OK. But what I need now is:

我必须相乘，取tensor-product，也称为alpha到LBR的向量的Kronecker product，alpha给出如下:

I have to multiply , take the tensor-product, also called Kronecker product of a vector called alpha to LBR, alpha is given as follows:

alpha = 0:0.1:2;

而且，我计算出的Kronecker product如下:

And, this Kronecker product I have computed as follows:

val = bsxfun(@times,LBR,permute(alpha,[3 1 2]));
LBR = reshape(permute(val,[1 3 2]),size(val,1)*size(val,3),[]);

我现在需要的是:我需要解决相同的min问题:

what I need now is: I need to solve the same minproblem:

[d,p] = min((LBR(:,1) - var1).^2 + (LBR(:,2) - var2).^2 + (LBR(:,3) - var3).^2);

但是，这次，除了从满足此min问题的L1和L2查找索引位置和值之外，我还需要找到单个索引的索引位置alpha向量中的"strong"值，该值已经相乘并且满足min问题.我不知道如何执行此操作，因此我们将不胜感激！

but, this time, in addition of finding the index-positions and values from L1 and L2 which satisfies this min-problem, I need to find the index position of the single value from the alpha vector which has been multiplied and which fulfills the min-problem. I don't have idea how can I do this so any help will be very appreciated!

提前谢谢！

Ps:如果需要，我可以发布L1和L2矩阵.

Ps: I can post the L1 and L2 matrices if needed.

推荐答案

我相信您需要在代码中进行此更正-

I believe you need this correction in your code -

[minindex_alongL2, minindex_alongL1] = ind2sub([size(L2,1) size(L1,1)],p)

对于该解决方案，您需要在最后一步中将p的大小添加到索引查找中，因为计算出min的向量具有alpha-

For the solution, you need to add the size of p into the index finding in the last step as the vector whose min is calculated has the "added influence" of alpha -

[minindex_alongL2, minindex_alongL1,minindex_alongalpha] = ind2sub([size(L2,1) size(L1,1) numel(alpha)],p)

minindex_alongalpha可能与您有关.

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