SVD_SMALLEST — SLEPc 3.25.0 documentation

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# SVD_SMALLEST

The solver is configured to compute smallest singular values.

## Note

Computing small singular values is generally more difficult than computing largest ones, because in many cases these values are very small and tightly clustered together. In the case of rank-deficient matrices, smallest singular values are zero, and this may pose difficulties to the solvers.

## See Also

SVD: Singular Value Decomposition, `SVDWhich`, `SVDSetWhichSingularTriplets()`, `SVD_LARGEST`

## Level

intermediate

## Location

include/slepcsvd.h

Index of all SVD routines Table of Contents for all manual pages Index of all manual pages