My particular application requires me to do the following:
- Take SVD decomposition of a slab of a tensor (lets call this tensor
F
of size[Nr,Nt,Nsub]
) - Get the right singular matrix of this slab (lets call it matrix
V
) - multiply the slab with subset of the right singular matrix
- Multiply the result by another vector (
s
of dimensionnx1
)
for k=1:size(F,3)
H= squeeze(F(:,:,k));
[U,Sigma,V]= svd(H);
V= V(:,1:n);
Y(:,k) = H * V* s;
end
My question is: does this matrix multiplication make any sense, or am I doing something wrong in the sense that I have implicity a three dimension matrix being multiplied by a 2 D matrices... in other words am I overwriting values?
If my question isnt clear I can edit it.. Thank you.