mpdn.m

来自「％ Atomizer Main Directory, Version .802 」· M 代码 · 共 64 行

function [xrec, coef] = MPDN(y, NameOfDict, par1, par2, par3)
% MPDN -- Matching Pursuit DeNoising (Forward Stepwise Regression)
%  Usage
%	[xrec, coef] = MPDN(y, NameOfDict, par1, par2, par3)
%  Inputs
%       y               1-d signal to be de-noised; column vector
%	NameOfDict	string; name of the dictionary
%	par1,par2,par3	parameters of the dictionary
%
%	Use 'help dictionary' for dictionary objects: NameOfDict,par1,par2,par3
%  Outputs
%       xrec            cleaned signal; column vector
%       coef            coeff of cleaned signal; column vector
%  Description
%	1. Assumes noise level == 1
%	2. MPDN runs MP until the coef of the selected atom is less than 
%	   the threshold sqrt(2 * log(m)), where m is the cardinality
%	   of the dictionary
%  See Also
%	MP
%

%Size of the problem
y = y(:);
n = length(y);
[m, L] = SizeOfDict(n, NameOfDict, par1, par2, par3);

%Set the threholding level
thresh = (2 * log(m)) ^ .5;

%Matching Pursuit with frac * norm(y) = thresh
zerosm = zeros(m,1);
nrm = norm(y);
resnorm = nrm;
amp = nrm;

residule = y;
coef = [];
index = [];
k = 0;
amp = 2 * thresh;
fprintf('\nMPDeNoise:\n')
while (amp > thresh),
	c = FastA(residule, NameOfDict, par1, par2, par3);
	[amp i] = max(abs(c));
	i = i(1);
	index = [index; i];
	coefnew = c(i);
	coef = [coef; coefnew];
	temp = zerosm; temp(i) = 1;
	residule = residule - coefnew * FastS(temp, n, NameOfDict, par1, par2, par3);
	resnorm = norm(residule);
	k = k + 1;
	disp(sprintf('Step%4g:  select = %5g     coef = %10.2e', k,i,coefnew));
end

h = length(coef);
coefbest = zeros(m, 1);
for i = 1:h,
	coefbest(index(i)) = coefbest(index(i)) + coef(i);
end
coef = coefbest;
xrec = FastS(coef, n, NameOfDict, par1, par2, par3);