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Construct vector `c` such that `b = conv(a,c) + r`.
Equivalent to polynomial division.
That is quite brief, but means that c has length N=length(b)-length(a)+1 and the first N entries of r (if one computes it) are zero (up to rounding errors). I'm not sure how this generalizes to matrices. If a is separable, one could separate the deconvolution into a row-wise and a column-wise step, but for general a, I don't know.
That said, a deconvolution in the MMSE sense (i.e. find c such that sum(abs2, b - conv(a,c)) is minimized) might be useful and would also have a more obvious generalization to matrices, but it's not deconv.
conv
happily accepts 2d arrays:However, the analogous operation for
deconv
throws an error:Would it be possible to implement
deconv
for arrays?The text was updated successfully, but these errors were encountered: