A New Gradient Method with an Optimal Stepsize Property
Computational Optimization and Applications
Modified SOR-like method for the augmented system
International Journal of Computer Mathematics - Celebrating the Life of David J. Evans
Analysis of the nonlinear Uzawa algorithm for symmetric saddle point problems
International Journal of Computer Mathematics
Application of modified homotopy perturbation method for solving the augmented systems
Journal of Computational and Applied Mathematics
An adaptive inverse iteration for Maxwell eigenvalue problem based on edge elements
Journal of Computational Physics
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Scientific Computing
A modified symmetric successive overrelaxation method for augmented systems
Computers & Mathematics with Applications
A class of new generalized AOR method for augmented systems
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Parameterized preconditioning for generalized saddle point problems arising from the Stokes equation
Journal of Computational and Applied Mathematics
Semi-convergence analysis of Uzawa methods for singular saddle point problems
Journal of Computational and Applied Mathematics
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In this paper, we propose an inexact Uzawa method with variable relaxation parameters for iteratively solving linear saddle-point problems. The method involves two variable relaxation parameters, which can be updated easily in each iteration, similar to the evaluation of the two iteration parameters in the conjugate gradient method. This new algorithm has an advantage over most existing Uzawa-type algorithms: it is always convergent without any a priori estimates on the spectrum of the preconditioned Schur complement matrix, which may not be easy to achieve in applications. The rate of the convergence of the inexact Uzawa method is analyzed. Numerical results of the algorithm applied for the Stokes problem and a purely linear system of algebraic equations are presented.