mrpt::math::CLevenbergMarquardt Class Reference

An implementation of the Levenberg-Marquardt algorithm for least-square minimization. More...

#include <mrpt/math/CLevenbergMarquardt.h>

Inheritance diagram for mrpt::math::CLevenbergMarquardt:

List of all members.

Classes
struct	TResultInfo
Static Public Member Functions
static void	execute (vector_double &out_optimal_x, const vector_double &x0, utils::TFunctor_retVecDbl_inp2VecDbl functor, const vector_double &increments, const vector_double &userParam, TResultInfo &out_info, bool verbose=false, const size_t &maxIter=200, const double tau=1e-3, const double e1=1e-8, const double e2=1e-8)
	Executes the LM-method, with derivatives estimated from "functor" Is a user-provided function which takes as input two vectors, in this order: x: The parameters to be optimized.

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Detailed Description

An implementation of the Levenberg-Marquardt algorithm for least-square minimization.

Refer to the wiki page for more details on the algorithm and usage.

Definition at line 46 of file CLevenbergMarquardt.h.

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Member Function Documentation

static void mrpt::math::CLevenbergMarquardt::execute	(	vector_double &	out_optimal_x,
		const vector_double &	x0,
		utils::TFunctor_retVecDbl_inp2VecDbl	functor,
		const vector_double &	increments,
		const vector_double &	userParam,
		TResultInfo &	out_info,
		bool	verbose = false,
		const size_t &	maxIter = 200,
		const double	tau = 1e-3,
		const double	e1 = 1e-8,
		const double	e2 = 1e-8
	)			[static]

Executes the LM-method, with derivatives estimated from "functor" Is a user-provided function which takes as input two vectors, in this order:

• x: The parameters to be optimized.

• userParam: The vector passed to the LM algorithm, unmodified. and must return the "error vector", or the error (not squared) in each measured dimension, so the sum of the square of that output is the overall square error.