I know how to solve the problem
Ax=B
with matlab, I just use mldivide
to obtain x: x=A\B
But what if I have multiple basis A_i
and multiple data B_i
but the nature of the problem suggests me that the solution x
must be the same for every i
?
You could try stacking the A matrices and B vectors to obtain a larger least squares system. That is, form
A = (A_1)
...
(A_n)
and
B = (B_1)
...
(B_n)
and then solve
A*x = B
in the least squares sense
The solution x to such a system will be the value that minimises
Sum{ || A_i*x - B_i ||^2 }