I'm trying to compute the null space of a matrix A with M < N, using the residual singular vectors of the SVD decomposition of A. However, as the SVD code doesn't allow M < N, I have to work on A tanspose. I could use the fact that if A' = U.S.V' then A = V.S.U' and return the last vectors of U, but U is actually truncated because we compute a thin SVD, so some (or all in case M is full rank) vectors of M's null space are lost.
I'm guessing that either the SVD code should support the case M < N or there should be an option to compute the full SVD decomposition. Or is there another alternative I could use ? thanks, Christophe _______________________________________________ Help-gsl mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-gsl
