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Approximate a convolution as a sum of separable convolutions
I want to compute the discrete convolution of two 3D arrays: $A(i, j, k) \ast B(i, j, k)$
Is there a general way to decompose the array $A$ into a sum of a small number of separable arrays? That is:
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solution to $\min \|A-BXC \|$
I have the following problem. Let $A$, $B$ $C$ be real-valued matrices of size $m \times q$, $m \times n$, $p\times q$ respectively. I would like to find matrix $X$ of size $n\times p$ and maximum ...