This structure defines the workspace variables for solving the non-linear LM optimization. More...

#include <ccl_learn_alpha.h>

Data Fields
int	dim_x
	The dimensionality of the state variable.

int	dim_u
	The dimensionality of the action space.

int	dim_n
	The number of data points.

int	dim_b
	The number of basis functions.

int	dim_k
	The dimensionality of the constraints.

double *	xc
	A copy of the initial model parameters.

double *	x
	The flattened and updated model parameters.

double *	xf
	The finalised model parameters.

double *	epsx
	The tolerence of the model paramters.

double	epsf
	The tolerence fo the objective functions.

double *	r
	The returned value of the residual error.

double *	J
	The jacobian at x.

double	S
	The sqaure root if x is taken.

double *	A
	The dot product of J_T and J.

double *	v
	The dot product of J_T and r.

double *	D
	Automatic scaling.

double	Rlo
	The lower bound of R.

double	Rhi
	The upper bound of R.

double	l
	The adaptive learning rate.

double	lc
	Handling situation when learning rate happends to be 0.

double *	d
	The parameter improvement gradient.

int	iter
	The iteration number.

int	r_ok
	check if the objective function is belowed the tolerence

int	x_ok
	check if the model parameters are belowed the tolerence

double *	xd
	The next x.

double *	rd
	The residual error at xd.

double	Sd
	The squared error if xd is taken.

double	dS
	The denomitor of the sqaured error is xd is taken.

double	R
	The reduction if xd is taken.

double	nu
	The coefficient of changing learning rate.

double *	d_T
	The matrix transpose of d.

double *	J_T
	The matrix transpose of J.

double *	tmp
	The temporal variable.

double *	rd_T
	The matrix transpose of rd.

gsl_matrix *	D_pinv
	The peudo-inverse of D.

gsl_vector *	A_d
	The A matrix at xd.

gsl_matrix *	A_inv
	The peudo-inverse of A.

gsl_vector *	A_inv_diag
	The vector of diagonal elements of A matrix.

gsl_vector *	r_T
	The vector transpose of r.

Detailed Description

This structure defines the workspace variables for solving the non-linear LM optimization.

This structure containts the memory of the workspace variables for sovling the non-linear LM optimization problem. It should always initialise with ccl_solve_lm_ws_alloc and destroy with ccl_solve_lm_ws_free.

The documentation for this struct was generated from the following file:

include/ccl_learn_alpha.h

Data Fields

Detailed Description