Algorithms for Inverse Eigenvalue Problems

Abstract

Two new algorithms based on QR decompositions (QRDs) (with column pivoting) are proposed for solving inverse eigenvalue problems, and under some non-singularity assumptions they are both locally quadratically convergent.
Several numerical tests are presented to illustrate their convergence behavior.