Diagonally scaled memoryless quasi–Newton methods with application to compressed sensing

<p style='text-indent:20px;'>Memoryless quasi–Newton updating formulas of BFGS (Broyden–Fletcher–Goldfarb–Shanno) and DFP (Davidon–Fletcher–Powell) are scaled using well-structured diagonal matrices. In the scaling approach, elements as well eigenvalues memoryless play significant roles. Convergence analysis given diagonally methods is discussed. At last, performance numerically tested on a set CUTEr problems compressed sensing problem.</p>