TY - JOUR
T1 - A Regularized Conjugate Gradient Method for Symmetric Positive Definite System of Linear Equations
AU - Bai , Zhong-Zhi
AU -  , Shao-Liang Zhang
JO - Journal of Computational Mathematics
VL - 4
SP - 437
EP - 448
PY - 2002
DA - 2002/08
SN - 20
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jcm/8930.html
KW - Conjugate gradient method, Symmetric positive definite matrix, Regularization, Ill-conditioned linear system.
AB - <p style="text-align: justify;">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 invoved 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.</p>