Dear Matlab Users,
I am trying to solve a few separate sets of Ax = B equations with A\B or mldivide(A,B). A and B store equations components in their corresponding slices.
This is feasible with a for loop. Could it be done faster in some other way, with vectorization?
num_slices = 5;
A = rand(6,6, num_slices);
x = zeros(num_slices,6);
B = rand(6,1,num_slices);
for ii=1:num_slices
x(ii,:) =(A(:,:,ii)\B(:,:,ii))';
end
x_alternative =(A\B)';
The error I get is obvious as I do not use the "\" operation correctly:
Arguments must be 2-D, or at least one argument must be scalar. Use LDIVIDE (.\) for elementwise left division.
I would appreciate your help and suggestions in this matter.
EDIT:
I know about the option to flatten everything to sparse matices as suggested a few years ago here:
It would be great to learn if anything changed significantly from that time. Thank you!
Regards,
Jakub Kaminski
