Computing Symmetric Rank-Revealing Decompositions via Triangular Factorization

We present a family of algorithms for computing symmetric rank-revealing VSV decompositions, based on triangular factorization of the matrix. The VSV decomposition consists of a middle symmetric matrix that reveals the numerical rank in having three blocks with small norm, plus an orthogonalmatrix whose columns span approximations to the numerical range and null space. We show that for semi-de nite matrices the VSV decomposition should be computed via the ULV decomposition, while for inde nite matrices it must be computed via a URV-like decomposition that involves hyperbolic rotations.