bcs.cpp File Reference

Implementation of Bayesian compressive sensing algorithm. More...

#include "stdlib.h"
#include "stdio.h"
#include "math.h"
#include "assert.h"
#include <sstream>
#include <fstream>
#include "bcs.h"
#include "tools.h"
#include "ftndefs.h"
#include "deplapack.h"
#include "arrayio.h"
#include "arraytools.h"

Functions
void	WBCS (Array2D< double > &PHI, Array1D< double > &y, Array1D< double > &sigma2, double eta, Array1D< double > &lambda_init, int adaptive, int optimal, double scale, int verbose, Array1D< double > &weights, Array1D< int > &used, Array1D< double > &errbars, Array1D< double > &basis, Array1D< double > &alpha, Array2D< double > &Sig)
	The implementation of the Bayesian Compressive Sensing algorithm using Laplace Priors.
void	BCS (Array2D< double > &PHI, Array1D< double > &y, double &sigma2, double eta, Array1D< double > &lambda_init, int adaptive, int optimal, double scale, int verbose, Array1D< double > &weights, Array1D< int > &used, Array1D< double > &errbars, Array1D< double > &basis, Array1D< double > &alpha, double &lambda)
	Essentially same functionality as WBCS, but slightly altered I/O.

Detailed Description

Implementation of Bayesian compressive sensing algorithm.

Function Documentation

BCS()

void BCS	(	Array2D< double > &	PHI,
		Array1D< double > &	y,
		double &	sigma2,
		double	eta,
		Array1D< double > &	lambda_init,
		int	adaptive,
		int	optimal,
		double	scale,
		int	verbose,
		Array1D< double > &	weights,
		Array1D< int > &	used,
		Array1D< double > &	errbars,
		Array1D< double > &	basis,
		Array1D< double > &	alpha,
		double &	lambda )

Essentially same functionality as WBCS, but slightly altered I/O.

Note

Kept for backward compatibility with PyUQTk and BCS tests

WBCS()

void WBCS	(	Array2D< double > &	PHI,
		Array1D< double > &	y,
		Array1D< double > &	sigma2,
		double	eta,
		Array1D< double > &	lambda_init,
		int	adaptive,
		int	optimal,
		double	scale,
		int	verbose,
		Array1D< double > &	weights,
		Array1D< int > &	used,
		Array1D< double > &	errbars,
		Array1D< double > &	basis,
		Array1D< double > &	alpha,
		Array2D< double > &	Sig )

The implementation of the Bayesian Compressive Sensing algorithm using Laplace Priors.

Implements weighted version of the original Bayesian Compressive Sensing algorithm.

Note

This function has been written relying on the algorithm and MATLAB code presented in http://ivpl.eecs.northwestern.edu/research/projects/bayesian-compressive-sensing-using-laplace-priors and references therein

Todo

The array manipulations are not optimized - perhaps they need to be reconsidered using, say, fortran matrix-vector manipulation routines