DGESVD Methods |
The DGESVD type exposes the following members.
Methods| Name | Description | |
|---|---|---|
 | Run | Purpose ======= DGESVD computes the singular value decomposition (SVD) of a real M-by-N matrix A, optionally computing the left and/or right singular vectors. The SVD is written A = U * SIGMA * transpose(V) where SIGMA is an M-by-N matrix which is zero except for its min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA are the singular values of A; they are real and non-negative, and are returned in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A. Note that the routine returns V**T, not V. |
Extension Methods| Name | Description | |
|---|---|---|
 | GetEnumNames | (Defined by General) |
| IsValidDouble | (Defined by General) |
See Also