- #1
Klandhee
- 7
- 0
Hi, my problem is simple enough to write down but (to me) seems quite difficult to solve.
My equation is as follows
A[x1 x2] = I.
Here I is some known matrix, and A is an operator which applies a shifting matrix and sums. That is A[x1 x2] = s1x1 + s2x2, where s1 and s2 are two shifting matrices (continuously it can be thought of as convolving with a delta function). x1 and x2 are two unknown matrices of the same dimension as I. Ultimately I wish to find a matrix form for A so that I can invert it and obtain x1 and x2
So as you can see [x1 x2] can be thought of as a "stack" of matrices, or a 3D matrix (or a tensor?). However I'm very unfamiliar with the mathematics of tensors so one idea I had was to convert x1 and x2 into columns (i.e., just shopping the matrix into slices and adding one ontop of the other). That way [x1 x2] would be a matrix, and I would have lost no information.
From here, however, I am very confused and not sure where to go.
If anyone has any ideas on what to do (or if this problem is impossible) it would be GREATLY appreciated, thanks!
My equation is as follows
A[x1 x2] = I.
Here I is some known matrix, and A is an operator which applies a shifting matrix and sums. That is A[x1 x2] = s1x1 + s2x2, where s1 and s2 are two shifting matrices (continuously it can be thought of as convolving with a delta function). x1 and x2 are two unknown matrices of the same dimension as I. Ultimately I wish to find a matrix form for A so that I can invert it and obtain x1 and x2
So as you can see [x1 x2] can be thought of as a "stack" of matrices, or a 3D matrix (or a tensor?). However I'm very unfamiliar with the mathematics of tensors so one idea I had was to convert x1 and x2 into columns (i.e., just shopping the matrix into slices and adding one ontop of the other). That way [x1 x2] would be a matrix, and I would have lost no information.
From here, however, I am very confused and not sure where to go.
If anyone has any ideas on what to do (or if this problem is impossible) it would be GREATLY appreciated, thanks!