Package | Description |
---|---|
cern.colt.matrix.tfloat.algo.solver |
Iterative solvers
BiCG - BiConjugate gradients.
BiCGstab - BiConjugate gradients stabilized.
CG - Conjugate gradients.
CGS - Conjugate gradients squared.
Chebyshev - The Chebyshev iteration for symmetrical, positive definite matrices.
GMRES - Generalized minimal residual using restart.
IR - Iterative refinement (Richardson's method).
QMR - Quasi-minimal residual.
HyBR - Hybrid Bidiagonalization Regularization.
MRNSD - Modified Residual Norm Steepest Descent.
CGLS - Conjugate Gradient for Least Squares.
|
Modifier and Type | Class and Description |
---|---|
class |
FloatBiCG
BiCG solver.
|
class |
FloatBiCGstab
BiCG stablized solver.
|
class |
FloatCG
Conjugate Gradients solver.
|
class |
FloatCGLS
CGLS is Conjugate Gradient for Least Squares method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise.
|
class |
FloatCGS
Conjugate Gradients squared solver.
|
class |
FloatChebyshev
Chebyshev solver.
|
class |
FloatGMRES
GMRES solver.
|
class |
FloatHyBR
HyBR is a Hybrid Bidiagonalization Regularization method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise The
method combines an iterative Lanczos Bidiagonalization (LBD) Method with an
SVD-based regularization method to stabilize the semiconvergence behavior
that is characteristic of many ill-posed problems.
|
class |
FloatIR
Iterative Refinement.
|
class |
FloatMRNSD
MRNSD is Modified Residual Norm Steepest Descent method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise.
|
class |
FloatQMR
Quasi-Minimal Residual method.
|
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