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Abstract

For iterative solution of symmetric systems  the conjugate gradient method (CG) is commonly used when A is positive definite, while the minimum residual method (MINRES) is typically reserved for indefinite systems. We investigate the sequence of approximate solutions  generated by each method and suggest that even if A is positive definite, MINRES may be preferable to CG if iterations are to be terminated early. In particular, we show for MINRES that the solution norms  are monotonically increasing when A is positive definite (as was already known for CG), and the solution errors  are monotonically decreasing. We also show that the backward errors for the MINRES iterates  are monotonically decreasing.

 

 

Keywords

Conjugate gradient method (CG) Conjugate residual method (CR) Iterative method Krylov subspace method Linear equations Minimum residual method (MINRES) Sparse matrix Trust-region method.

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