A REGULARIZED CONJUGATE GRADIENT METHOD FOR SYMMETRIC POSITIVE DEFINITE SYSTEM OF LINEAR EQUATIONS

摘要

A class of regularized conjugate gradient methods is presented for solving the large sparse system of linear equations of which the coefficient matrix is an ill-conditioned sym- metric positive definite matrix. the convergence properties of these methods are discussed in depth, and the best possible choices o the parameters involved in the new methods are investigated in detail. Numerical computations show that the new methods are more effi- cient and robust than both classical relaxation methods and classical conjugate direction methods.