thresh.m

Matlab时频分析工具箱,希望能对大家有所帮助啊

function [xo,N]=thresh(ttype,xi,lambda,mtype);
%THRESH   Threshold (hard/soft)
%   Usage:  x=thresh(ttype,x,lambda);
%           [x,N]=thresh(ttype,x,lambda);
%           x=thresh(ttype,x,lambda,mtype);
%           [x,N]=thresh(ttype,x,lambda,mtype);
%
%   THRESH('hard',x,lambda) or THRESH(1,x,lambda) will perform
%   hard thresholding on x, i.e. all element with absolute value
%   less than lambda will be set to zero.
%
%   THRESH('soft',x,lambda) or THRESH(2,x,lambda) will perform
%   soft thresholding on x, i.e. lambda will be subtracted from
%   the absolute value of every element of x.
%
%   [x,N]=THRESH(ttype,x,lambda) additionally returns a number N specifying
%   how many numbers where kept.
%
%   THRESH(ttype,x,lambda,'full') returns the output as a full matrix. This
%   is the default.
%
%   THRESH(ttype,x,lambda,'sparse') returns the output as a sparse matrix.
%
%   The function WTHRESH in the Matlab Wavelet toolbox implements the same
%   functionality.
%

% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
% 
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
% 
% You should have received a copy of the GNU General Public License
% along with this program.  If not, see <http://www.gnu.org/licenses/>.

error(nargchk(3,4,nargin));

if (prod(size(lambda))~=1 || ~isnumeric(lambda))
  error('lambda must be a scalar.');
end;

if ischar(ttype)
  ttype=lower(ttype);
end;

dosparse=0;
if nargin==4
  switch(lower(mtype))
    case {'full'}
    case {'sparse'}
      if ndims(xi)>2
	error('Sparse output is only supported for 1D/2D input. This is a limitation of Matlab/Octave.');
      end;
      dosparse=1;      
    otherwise
      error('The output type (last argument) must be either "full" or "sparse".');
  end;
end;

signifmap=find(abs(xi)>=lambda);

if dosparse
  xo=sparse(size(xi,1),size(xi,2));
else
  xo=zeros(size(xi));
end;

switch ttype
  case {'hard',1}
    xo(signifmap)=xi(signifmap);
  case {'soft',2}
    xo(signifmap)=xi(signifmap) - sign(signifmap)*lambda;
  otherwise
    error('Unknown thresholding type.');
end;

if nargout==2
  N=sum(signifmap(:));
end;

% Another way to do hard threshholding.
% xo=xi.*(abs(xi)>=lambda);

% Another way to do soft threshholding
%xa=abs(xi)-lambda;
% In the following line, the +0 is significant: It turns
% -0 into +0, oh! the joy of numerics.
%xo=((xa>0).*xa+0).*sign(xi);