Newton-like iteration based on a cubic polynomial for structured matrices
Matrices with a low displacement rank are considered. A new Newton-like iteration for computing the Moore-Penrose generalized inverses of such matrices is presented, which is based on a cubic polynomial. Numerical experiments for Toeplitz-like and Cauchy-like matrices show its efficiency and enigmatic effect of the improvement of approximation by compression in the case of structured input.
scientific article; zbMATH DE number 2145929