public class SuccessiveOverrelaxationSolver extends Object implements IterativeLinearSystemSolver
ωopt = 2 / (1 + sqrt(1 - ρ2))This is seldom done, since calculating the spectral radius of the Jacobi matrix requires an impractical amount of computation. However, relatively inexpensive rough estimates of ρ can yield reasonable estimates for the optimal value of ω. This implementation does not support preconditioning.
IterativeLinearSystemSolver.Solution| Constructor and Description |
|---|
SuccessiveOverrelaxationSolver(double omega,
int maxIteration,
Tolerance tolerance)
Construct a SOR solver with the extrapolation factor ω.
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| Modifier and Type | Method and Description |
|---|---|
IterativeLinearSystemSolver.Solution |
solve(LSProblem problem) |
IterativeLinearSystemSolver.Solution |
solve(LSProblem problem,
IterationMonitor<Vector> monitor)
Solves iteratively
Ax = b
until the solution converges, i.e., the norm of residual
(b - Ax) is less than or equal to the threshold.
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public SuccessiveOverrelaxationSolver(double omega,
int maxIteration,
Tolerance tolerance)
omega - the extrapolation factormaxIteration - the maximum number of iterationstolerance - the convergence thresholdpublic IterativeLinearSystemSolver.Solution solve(LSProblem problem) throws ConvergenceFailure
ConvergenceFailurepublic IterativeLinearSystemSolver.Solution solve(LSProblem problem, IterationMonitor<Vector> monitor) throws ConvergenceFailure
IterativeLinearSystemSolverAx = buntil the solution converges, i.e., the norm of residual (b - Ax) is less than or equal to the threshold.
solve in interface IterativeLinearSystemSolverproblem - a system of linear equationsmonitor - an iteration monitorConvergenceFailure - if the algorithm fails to convergeCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.