Lines Matching full:singular
448 * the diagonal entries of S are known as the \em singular \em values of \a A and the columns of \a U and \a V are known as the left
449 * and right \em singular \em vectors of \a A respectively.
451 * Singular values are always sorted in decreasing order.
453 * This JacobiSVD decomposition computes only the singular values by default. If you want \a U or \a V, you need to ask for them explicitly.
456 * smaller value among \a n and \a p, there are only \a m singular vectors; the remaining columns of \a U and \a V do not correspond to actual
457 * singular vectors. Asking for \em thin \a U or \a V means asking for only their \a m first columns to be formed. So \a U is then a n-by-m matrix,
739 /*** step 3. The work matrix is now diagonal, so ensure it's positive so its diagonal entries are the singular values ***/
763 /*** step 4. Sort singular values in descending order and compute the number of nonzero singular values ***/
790 * \return the singular value decomposition of \c *this computed by two-sided
