A new algorithm for computing the extreme eigenvectors of a complex hermitian matrix

Abstract

An algorithm was presented for computing the eigenvector associated with either the largest or the smallest eigenvalue of a complex Hermitian matrix. The optimal step size was calculated and a global convergence proof was given. Simulations showed that unlike classical algorithms for finding extremal eigenvectors, the convergence rate of the proposed method was relatively insensitive to the eigenvalue distribution.