A choice of forcing terms in inexact Newton method
Journal of Computational and Applied Mathematics
A globally convergent Newton-GMRES method for large sparse systems of nonlinear equations
Applied Numerical Mathematics
Journal of Computational Physics
Journal of Computational and Applied Mathematics
On the linear convergence of Newton-Krylov methods
Optimization Methods & Software - THE JOINT EUROPT-OMS CONFERENCE ON OPTIMIZATION, 4-7 JULY, 2007, PRAGUE, CZECH REPUBLIC, PART II
On choosing a nonlinear initial iterate for solving the 2-D 3-T heat conduction equations
Journal of Computational Physics
Hybrid spectral gradient method for the unconstrained minimization problem
Journal of Global Optimization
Solution of systems of nonlinear equations -- a semi-implicit approach
Applied Numerical Mathematics
Nonsymmetric Preconditioner Updates in Newton-Krylov Methods for Nonlinear Systems
SIAM Journal on Scientific Computing
Nonmonotone spectral method for large-scale symmetric nonlinear equations
Numerical Algorithms
Journal of Computational Physics
Perceptual radiometric compensation for inter-reflection in immersive projection environment
Proceedings of the 19th ACM Symposium on Virtual Reality Software and Technology
Hi-index | 0.02 |
Newton--Krylov methods are variants of inexact Newton methods where the approximate Newton direction is taken from a subspace of small dimension. Here we introduce a new hybrid Newton-GMRES method where a global strategy restricted to a low-dimensional subspace generated by GMRES is performed. The obtained process is consistent with preconditioning and with matrix-free implementation. Computational results indicate that our proposal enhances the classical backtracking inexact method.