摘要

Recently, some novel variants of Lanczos-type methods were explored that are based on the biconjugate A-orthonormalization process. Numerical experiments coming from some physical problems indicate that these new methods are competitive with or superior to other popular Krylov subspace methods. Among them, the biconjugate A-orthogonal residual (BiCOR) method is the archetype method. However, like the biconjugate gradient (BiCG) method, the BiCOR method often shows irregular convergence behavior which can lead to numerical instability. To overcome this drawback, motivated by the effectiveness and robustness of the quasi-minimal residual (QMR) method, we derive a new QMR-like approach based on the coupled two-term biconjugate A-orthonormalization process and simple recurrences instead of the QR decomposition. Some convergence properties are given, and the special case for solving complex symmetric linear system is considered. Finally, numerical experiments are reported to illustrate the performances of our methods and their preconditioners on linear systems discretizing the Helmholtz equation or taken from Florida Sparse Matrix Collection.