document: A regularized conjugate gradient method for symmetric positive definite system of linear equations 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 symmetric positive definite matrix . The convergence properties of these methods are discussed in depth , and the best possible choices of the parameters involved in the new methods are investigated in detail . Numerical computations show that the new methods are more efficient and robust than both classical relaxation methods and classical conjugate direction methods
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