joptimization.hpp File Reference

This is the standard header defined in jafar to use non linear optimaztion methods Code spoofed from Cyrille Berger (cberger@cberger.net) More...

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Detailed Description

This is the standard header defined in jafar to use non linear optimaztion methods Code spoofed from Cyrille Berger (cberger@cberger.net)

Definition in file joptimization.hpp.

Go to the source code of this file.

Classes
struct	joptimization::methods::GaussNewton< _TFunction_, _TType_ >
	Use this class as a template parameter for the gaussNewton function if you want to use the Gauss-Newton method which uses only the jacobian. More...
struct	joptimization::methods::Newton< _TFunction_, _TType_ >
	Use this class as a template parameter for the gaussNewton function if you want to use the Newton method which uses the Hessian. More...
Namespaces
namespace	joptimization
	shortcut for ublas namespace
namespace	joptimization::algorithms
	This namespace contains function to call some of the classical optimization algorithm for estimating the parameter p and minimizing sum( f_i(p)2 ).
Functions
template<class _TFunction_ , typename _TType_ >
_TType_	joptimization::algorithms::gradientDescent (_TFunction_ *f, ublas::vector< _TType_ > &parameters, int iter, _TType_ epsilon, _TType_ gamma)
	Perform an optimization following Gauss Newton algorithm.
template<class _TMethod_ >
_TMethod_::Type	joptimization::algorithms::gaussNewton (typename _TMethod_::Function *f, ublas::vector< typename _TMethod_::Type > &parameters, int iter, typename _TMethod_::Type epsilon)
	Perform an optimization following Gauss Newton algorithm.
template<class _TFunction_ , typename _TType_ >
_TType_	joptimization::algorithms::levenbergMarquardt (_TFunction_ *f, ublas::vector< _TType_ > &parameters, int iter, _TType_ epsilon, _TType_ lambda0, _TType_ nu)
	Perform an optimization following Levenberg Marquardt algorithm.
template<typename _TType_ >
double	optimization::details::computeRemain (const ublas::vector< _TType_ > &values)
template<typename _TType_ >
ublas::vector< double >	optimization::details::solve (const ublas::matrix< _TType_ > &M, const ublas::matrix< _TType_ > &jacobian, const ublas::vector< _TType_ > &values, int p_count)