Blog

Matrix decompositions play a central role in matrix computations. In this talk, we comment on the history of some widely used decompositions such as Cholesky decomposition; LU decomposition; QR decomposition; eigenvalue decomposition and singular value decomposition. Subsequently we take the QR algorithm and the Arnoldi iteration as examples to demonstrate the applications of the QR decomposition in matrix computations. Finally we present a novel matrix decomposition in pseudospectral methods.