Solve AX=B using singular value decomposition
Math Functions / Matrices and Linear Algebra / Linear System Solvers
dspsolvers
The SVD Solver block solves the linear system AX=B, which can be overdetermined, underdetermined, or exactly determined. The system is solved by applying singular value decomposition (SVD) factorization to the MbyN matrix A, at the A port. The input to the B port is the right side MbyL matrix, B. The block treats lengthM unoriented vector input as an Mby1 matrix.
The output at the X port is the NbyL matrix, X. X is chosen to minimize the sum of the squares of the elements of BAX (the residual). When B is a vector, this solution minimizes the vector 2norm of the residual. When B is a matrix, this solution minimizes the matrix Frobenius norm of the residual. In this case, the columns of X are the solutions to the L corresponding systems AX_{k}=B_{k}, where B_{k} is the kth column of B, and X_{k} is the kth column of X.
X is known as the minimumnormresidual solution to AX=B. The minimumnormresidual solution is unique for overdetermined and exactly determined linear systems, but it is not unique for underdetermined linear systems. Thus when the SVD Solver block is applied to an underdetermined system, the output X is chosen such that the number of nonzero entries in X is minimized.
Select to enable the E output port, which reports a failure to converge. The possible values you can receive on the port are:
0
— The singular value decomposition
calculation converges.
1
— The singular value decomposition
calculation does not converge.
If the singular value decomposition calculation fails to converge, the output at port X is an undefined matrix of the correct size.
Port  Supported Data Types 

A 

B 

X 

E 

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