slepc-3.11.2 2019-07-30
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Singular Value Decomposition Solvers - SVD: Examples

The Singular Value Decomposition Solver (SVD) is very similar to the EPS object, but intended for the computation of the partial SVD of a rectangular matrix. With this type of object, the user can specify an SVD problem and solve it with any of the different solvers encapsulated by the package. Some of these solvers are actually implemented through calls to EPS eigensolvers.

The user interface is very similar to that of EPS, both for the options database (e.g., -svd_nsv 4 -svd_type lanczos), and for the programmatic interface (e.g., SVDSetDimensions() / SVDSetType()).

ex8.c: Estimates the 2-norm condition number of a matrix A, that is, the ratio of the largest to the smallest singular values of A
ex14.c: Solves a singular value problem with the matrix loaded from a file
ex15.c: Singular value decomposition of the Lauchli matrix
makefile