comparison solvers/SMALL_chol.m @ 128:8e660fd14774 ivand_dev

Feature 186
author Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk>
date Mon, 13 Jun 2011 14:55:45 +0100
parents f6cedfec9ffb
children
comparison
equal deleted inserted replaced
126:db5a7fe1a404 128:8e660fd14774
1 function [A]=SMALL_chol(Dict,X, m, maxNumCoef, errorGoal, varargin) 1 function [A]=SMALL_chol(Dict,X, m, maxNumCoef, errorGoal, varargin)
2 %% 2 %% Implementation of OMP with Cholesky factorisation
3 % Sparse coding of a group of signals based on a given
4 % dictionary and specified number of atoms to use.
5 % input arguments: Dict - the dictionary
6 % X - the signals to represent
7 % m - number of atoms in Dictionary
8 % errorGoal - the maximal allowed representation error for
9 % each signal.
10 %
11 % optional: if Dict is function handle then Transpose Dictionary
12 % handle needs to be specified.
13 %
14 % output arguments: A - sparse coefficient matrix.
15 %
16
3 % 17 %
4 % Centre for Digital Music, Queen Mary, University of London. 18 % Centre for Digital Music, Queen Mary, University of London.
5 % This file copyright 2009 Ivan Damnjanovic. 19 % This file copyright 2009 Ivan Damnjanovic.
6 % 20 %
7 % This program is free software; you can redistribute it and/or 21 % This program is free software; you can redistribute it and/or
8 % modify it under the terms of the GNU General Public License as 22 % modify it under the terms of the GNU General Public License as
9 % published by the Free Software Foundation; either version 2 of the 23 % published by the Free Software Foundation; either version 2 of the
10 % License, or (at your option) any later version. See the file 24 % License, or (at your option) any later version. See the file
11 % COPYING included with this distribution for more information. 25 % COPYING included with this distribution for more information.
12 % 26 %
13 % Sparse coding of a group of signals based on a given
14 % dictionary and specified number of atoms to use.
15 % input arguments: Dict - the dictionary
16 % X - the signals to represent
17 % m - number of atoms in Dictionary
18 % errorGoal - the maximal allowed representation error for
19 % each signal.
20 %
21 % optional: if Dict is function handle then Transpose Dictionary
22 % handle needs to be specified.
23 %
24 % output arguments: A - sparse coefficient matrix.
25 %
26 %% 27 %%
27 % This Dictionary check is based on Thomas Blumensath work in sparsify 0_4 greedy solvers 28 % This Dictionary check is based on Thomas Blumensath work in sparsify 0_4 greedy solvers
28 explicitD=0; 29 explicitD=0;
29 if isa(Dict,'float') 30 if isa(Dict,'float')
30 D =@(z) Dict*z; 31 D =@(z) Dict*z;