Matrix indexing: fast way to compute covariance of N different MxL matrices that are saved in NxMxL matrix

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T
T am 24 Mär. 2017
Bearbeitet: Matt J am 24 Mär. 2017
I have a NxMxL matrix called bigmatrix That I can split into N temporary submatrices. On each temporary submatrix I need to calculate the covariance. I do this in the following way:
for k=1:N
submatrix=squeeze(bigmatrix(k,:,:)).';
R=submatrix*submatrix';
end
The covariance is calculated really fast. My problem is loading the submatrix. This takes 6 seconds. Is there a faster way to do this? The matrix indexing is slowing me down a lot.
Thanks!

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Antworten (1)

Matt J
Matt J am 24 Mär. 2017
Bearbeitet: Matt J am 24 Mär. 2017
Using MTIMESX ( Download ), we can eliminate the loop altogether,
data=permute(bigmatrix,[2,3,1]);
R=mtimesx(data,'t',data);
If you build bigmatrix as MxLxN in the first place, you can avoid the overhead of permute(). Even without mtimesx, I expect an MxLxN data organization will accelerate your loop
for k=1:N
submatrix=data(:,:,k);
R=submatrix.'*submatrix;
end

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