HCL_EvalLSFcnlGN_d is the evaluation object for the functional class HCL_LeastSquareFcnlGN_d, which implements a least-squares functional based on a nonlinear operator
![]() | HCL_EvalLSFcnlGN_d (const HCL_Vector_d & Input, HCL_LinearOp_d * Operator, HCL_Vector_d * Data, double PenaltyParameter, HCL_LinearOp_d * RegularizingOperator, HCL_Vector_d * ModelPrior) Usual constructor for linear operator input |
![]() | HCL_EvalLSFcnlGN_d (const HCL_Vector_d & Input, HCL_Op_d * Operator, HCL_Vector_d * Data, double PenaltyParameter, HCL_LinearOp_d * RegularizingOperator, HCL_Vector_d * ModelPrior) Usual constructor for nonlinear operator input |
![]() | Domain () const Domain space access |
![]() | Value () const Value returns the values of the functional at the given point. |
![]() | Gradient ( HCL_Vector_d & g ) const Gradient assigns to g the gradient of the functional. |
![]() | Hessian () const Hessian creates the Hessian operator. |
![]() | Write ( ostream & str ) const Write prints a description of the object. |
HCL_EvalLSFcnlGN_d is the evaluation object for the functional class HCL_LeastSquareFcnlGN_d, which implements a least-squares functional based on a nonlinear operator. The suffix "GN" indicates that the Gauss-Newton approximation to the Hessian is used. See the documentation for HCL_LeastSquaresFcnlGN_d and HCL_EvaluateFunctional_d for more information.
HCL_EvalLSFcnlGN_d(const HCL_Vector_d & Input, HCL_Op_d * Operator, HCL_Vector_d * Data, double PenaltyParameter, HCL_LinearOp_d * RegularizingOperator, HCL_Vector_d * ModelPrior)
virtual HCL_VectorSpace_d& Domain() const
virtual double Value() const
virtual void Gradient( HCL_Vector_d & g ) const
virtual HCL_LinearOp_d* Hessian() const
virtual ostream& Write( ostream & str ) const
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