Lines Matching refs:Matrix
29 * SVD decomposition consists in decomposing any n-by-p matrix \a A as a product
31 * where \a U is a n-by-n unitary, \a V is a p-by-p unitary, and \a S is a n-by-p real positive matrix which is zero outside of its main diagonal;
38 * You can ask for only \em thin \a U or \a V to be computed, meaning the following. In case of a rectangular n-by-p matrix, letting \a m be the
40 * 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,
41 * and \a V is then a p-by-m matrix. Notice that thin \a U and \a V are all you need for (least squares) solving.
43 * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
67 typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixUType;
68 typedef Matrix<Scalar, ColsAtCompileTime, ColsAtCompileTime, MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTime> MatrixVType;
74 /** \returns the \a U matrix.
76 * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
77 * the U matrix is n-by-n if you asked for \link Eigen::ComputeFullU ComputeFullU \endlink, and is n-by-m if you asked for \link Eigen::ComputeThinU ComputeThinU \endlink.
79 * The \a m first columns of \a U are the left singular vectors of the matrix being decomposed.
90 /** \returns the \a V matrix.
92 * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p,
93 * the V matrix is p-by-p if you asked for \link Eigen::ComputeFullV ComputeFullV \endlink, and is p-by-m if you asked for \link Eigen::ComputeThinV ComputeThinV \endlink.
95 * The \a m first columns of \a V are the right singular vectors of the matrix being decomposed.
108 * For the SVD decomposition of a n-by-p matrix, letting \a m be the minimum of \a n and \a p, the
124 /** \returns the rank of the matrix of which \c *this is the SVD.
266 Matrix<Scalar, Dynamic, RhsType::ColsAtCompileTime, 0, MatrixType::MaxRowsAtCompileTime, RhsType::MaxColsAtCompileTime> tmp;
299 "SVDBase: thin U and V are only available when your matrix has a dynamic number of columns.");
