If you have a matrix A and apply singular value decomposition, the three results are a matrix U, a vector s ("singular"), and a matrix Vh, such that A = U * S * Vh. The S term is a matrix that has the ...

For a (row) diagonally dominant matrix, if all of its off-diagonal entries and its diagonally dominant parts (which are defined for each row as the absolute value of the diagonal entry subtracted by ...

The singular value decomposition of a matrix is used to derive systematically the Moore-Penrose inverse for a matrix bordered by a row and a column, in addition to the Moore-Penrose inverse for the ...