contrib/brl/bbas/bsta/algo/bsta_gaussian_updater.h File Reference

Iterative updating of Gaussians. More...

#include <bsta/bsta_gaussian_sphere.h>
#include <bsta/bsta_gaussian_indep.h>
#include <bsta/bsta_gaussian_full.h>
#include <bsta/bsta_mixture.h>
#include <bsta/bsta_attributes.h>
#include <vcl_algorithm.h>

Go to the source code of this file.

Classes
class	bsta_gaussian_updater< gauss_ >
	An updater for statistically updating Gaussian distributions. More...
class	bsta_gaussian_window_updater< gauss_ >
	An updater for updating Gaussian distributions with a moving window. More...
Functions
template<class T >
void	bsta_update_gaussian (bsta_gaussian_sphere< T, 1 > &gaussian, T rho, const T &sample)
	Update the statistics given a 1D Gaussian distribution and a learning rate.
template<class T , unsigned n>
void	bsta_update_gaussian (bsta_gaussian_sphere< T, n > &gaussian, T rho, const vnl_vector_fixed< T, n > &sample)
	Update the statistics given a Gaussian distribution and a learning rate.
template<class T , unsigned n>
void	bsta_update_gaussian (bsta_gaussian_indep< T, n > &gaussian, T rho, const vnl_vector_fixed< T, n > &sample)
	Update the statistics given a Gaussian distribution and a learning rate.
template<class T , unsigned n>
void	bsta_update_gaussian (bsta_gaussian_full< T, n > &gaussian, T rho, const vnl_vector_fixed< T, n > &sample)
	Update the statistics given a Gaussian distribution and a learning rate.
template<class T >
T	element_max (const T &a, const T &b)
template<class T , unsigned n>
vnl_vector_fixed< T, n >	element_max (const vnl_vector_fixed< T, n > &a_vector, const T &b)
	element-wise minimum of vector.
template<class T , unsigned n>
vnl_vector_fixed< T, n >	element_max (const vnl_vector_fixed< T, n > &a_vector, const vnl_vector_fixed< T, n > &b_vector)
	element-wise minimum of vector.
template<class T , unsigned n>
vnl_matrix_fixed< T, n, n >	element_max (const vnl_matrix_fixed< T, n, n > &a_matrix, const T &b)
	element-wise minimum on the matrix diagonal.
template<class T , unsigned n>
vnl_matrix_fixed< T, n, n >	element_max (const vnl_matrix_fixed< T, n, n > &a_matrix, const vnl_matrix_fixed< T, n, n > &b_matrix)
	element-wise minimum of matrix.
template<class gauss_ >
void	bsta_update_gaussian (gauss_ &gaussian, typename gauss_::math_type rho, const typename gauss_::vector_type &sample, const typename gauss_::covar_type &min_covar)
	Update the statistics given a Gaussian distribution and a learning rate.
template<class T , unsigned n>
void	bsta_update_gaussian (bsta_gaussian_indep< T, n > &gaussian, T rho, const vnl_vector_fixed< T, n > &sample, T min_var)
	Update the statistics given a Gaussian distribution and a learning rate.
template<class T , unsigned n>
void	bsta_update_gaussian (bsta_gaussian_full< T, n > &gaussian, T rho, const vnl_vector_fixed< T, n > &sample, T min_var)
	Update the statistics given a Gaussian distribution and a learning rate.

---

Detailed Description

Iterative updating of Gaussians.

Author:

Matt Leotta (mleotta@lems.brown.edu)

Date:

February 22, 2006

    Modifications
     Jun 18, 2008 - Matt Leotta -- Adjusted such that min_var is a hard minimum
                                   instead of a minimum in the limit
   

Definition in file bsta_gaussian_updater.h.

---

Function Documentation

template<class T >

void bsta_update_gaussian	(	bsta_gaussian_sphere< T, 1 > &	gaussian,
		T	rho,
		const T &	sample
	)

Update the statistics given a 1D Gaussian distribution and a learning rate.

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 27 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

void bsta_update_gaussian	(	bsta_gaussian_sphere< T, n > &	gaussian,
		T	rho,
		const vnl_vector_fixed< T, n > &	sample
	)

Update the statistics given a Gaussian distribution and a learning rate.

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 47 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

void bsta_update_gaussian	(	bsta_gaussian_indep< T, n > &	gaussian,
		T	rho,
		const vnl_vector_fixed< T, n > &	sample
	)

Update the statistics given a Gaussian distribution and a learning rate.

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 67 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

void bsta_update_gaussian	(	bsta_gaussian_full< T, n > &	gaussian,
		T	rho,
		const vnl_vector_fixed< T, n > &	sample
	)

Update the statistics given a Gaussian distribution and a learning rate.

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 88 of file bsta_gaussian_updater.h.

template<class gauss_ >

void bsta_update_gaussian	(	gauss_ &	gaussian,
		typename gauss_::math_type	rho,
		const typename gauss_::vector_type &	sample,
		const typename gauss_::covar_type &	min_covar
	)		[inline]

Update the statistics given a Gaussian distribution and a learning rate.

Parameters:

min_covar

forces the covariance to stay above this limit

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 183 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

void bsta_update_gaussian	(	bsta_gaussian_indep< T, n > &	gaussian,
		T	rho,
		const vnl_vector_fixed< T, n > &	sample,
		T	min_var
	)		[inline]

Update the statistics given a Gaussian distribution and a learning rate.

Parameters:

min_var

forces all the variances to stay above this limit

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 197 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

void bsta_update_gaussian	(	bsta_gaussian_full< T, n > &	gaussian,
		T	rho,
		const vnl_vector_fixed< T, n > &	sample,
		T	min_var
	)		[inline]

Update the statistics given a Gaussian distribution and a learning rate.

Parameters:

min_var

forces the diagonal covariance to stay above this limit

Note:

if rho = 1/(num observations) then this just an online cumulative average

Definition at line 210 of file bsta_gaussian_updater.h.

template<class T >

T element_max	(	const T &	a,
		const T &	b
	)		[inline]

Definition at line 113 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

vnl_vector_fixed<T,n> element_max	(	const vnl_vector_fixed< T, n > &	a_vector,
		const T &	b
	)

element-wise minimum of vector.

Definition at line 121 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

vnl_vector_fixed<T,n> element_max	(	const vnl_vector_fixed< T, n > &	a_vector,
		const vnl_vector_fixed< T, n > &	b_vector
	)

element-wise minimum of vector.

Definition at line 135 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

vnl_matrix_fixed<T,n,n> element_max	(	const vnl_matrix_fixed< T, n, n > &	a_matrix,
		const T &	b
	)

element-wise minimum on the matrix diagonal.

Definition at line 150 of file bsta_gaussian_updater.h.

template<class T , unsigned n>

vnl_matrix_fixed<T,n,n> element_max	(	const vnl_matrix_fixed< T, n, n > &	a_matrix,
		const vnl_matrix_fixed< T, n, n > &	b_matrix
	)

element-wise minimum of matrix.

Definition at line 165 of file bsta_gaussian_updater.h.