Abstract For solving non-Hermitian linear systems, a famous method is Bi-Conjugate Gradient method (Bi-CG), but its performance is not usually satisfactory because of the unstable convergent behavior and the expensive computational cost. Recently a family of methods named Product-type methods were developed to enhance the Bi-CG method by redefining the residual vector as rn: = Hn(A)r B n, where
Starting from a specific implementation of the Lanczos biorthogonalization algorithm, an iterative p...
AbstractThe Conjugate Gradient Squared (CGS) is an iterative method for solving nonsymmetric linear ...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...
The numerical methods for solving linear systems have come to play an important role in various fiel...
AbstractIn the present paper, a class of product-type Krylov-subspace methods for solving nonsymmetr...
AbstractThe Conjugate Gradient (CG) method and the Conjugate Residual (CR) method are Krylov subspac...
. The Conjugate Gradient Squared (CGS) is a well-known and widely used iterative method for solving ...
In the present paper, we introduce a new extension of the conjugate residual (CR) method for solving...
AbstractWe propose Bi-Conjugate Residual (BiCR) variants of the hybrid Bi-Conjugate Gradient (BiCG) ...
We propose Bi-Conjugate Residual (BiCR) variants of the hybrid Bi-Conjugate Gradient (BiCG) methods ...
AbstractThe global bi-conjugate gradient (Gl-BCG) method is an attractive matrix Krylov subspace met...
In this study, we derive a new iterative algorithm (including its preconditioned version) which is a...
Abstarct. Recently S.-L. Zhang has proposed a unification and generalization of results involving pr...
In the present paper, we introduce a new extension of the conjugate residual (CR) method for solving...
The Lanczos algorithm can be used both for eigenvalue problems and to solve linear systems. However,...
Starting from a specific implementation of the Lanczos biorthogonalization algorithm, an iterative p...
AbstractThe Conjugate Gradient Squared (CGS) is an iterative method for solving nonsymmetric linear ...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...
The numerical methods for solving linear systems have come to play an important role in various fiel...
AbstractIn the present paper, a class of product-type Krylov-subspace methods for solving nonsymmetr...
AbstractThe Conjugate Gradient (CG) method and the Conjugate Residual (CR) method are Krylov subspac...
. The Conjugate Gradient Squared (CGS) is a well-known and widely used iterative method for solving ...
In the present paper, we introduce a new extension of the conjugate residual (CR) method for solving...
AbstractWe propose Bi-Conjugate Residual (BiCR) variants of the hybrid Bi-Conjugate Gradient (BiCG) ...
We propose Bi-Conjugate Residual (BiCR) variants of the hybrid Bi-Conjugate Gradient (BiCG) methods ...
AbstractThe global bi-conjugate gradient (Gl-BCG) method is an attractive matrix Krylov subspace met...
In this study, we derive a new iterative algorithm (including its preconditioned version) which is a...
Abstarct. Recently S.-L. Zhang has proposed a unification and generalization of results involving pr...
In the present paper, we introduce a new extension of the conjugate residual (CR) method for solving...
The Lanczos algorithm can be used both for eigenvalue problems and to solve linear systems. However,...
Starting from a specific implementation of the Lanczos biorthogonalization algorithm, an iterative p...
AbstractThe Conjugate Gradient Squared (CGS) is an iterative method for solving nonsymmetric linear ...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...