ivan@155: function [X , cost] = wrapper_mm_solver(b, A, param)
aris@211: %% SMALL wrapper for Majorization Minimization toolbox solver
ivan@155: %
ivan@155: %   Function gets as input
ivan@155: %       b - measurement vector 
ivan@155: %       A - dictionary 
aris@219: %       param - structure containing additional parameters. These are:
aris@219: %           - initcoeff   Initial guess for the coefficients
aris@219: %                         (optional)
aris@219: %           - to          1/(step size). It is larger than spectral norm
aris@219: %                         of dictionary A (default is 0.1+(svds(A,1))^2)
aris@219: %           - lambda      Lagrangian multiplier. Regulates shrinkage
aris@219: %                         (default is 0.4)
aris@219: %           - iternum     Inner-loop maximum iteration number 
aris@219: %                         (default is 1000)
aris@219: %           - epsilon     Stopping criterion for iterative softthresholding
aris@219: %                         (default is 1e-7)
aris@219: %           - map         Debiasing. 0 = No, 1 = Yes (default is 0)
aris@219: %
ivan@155: %   Output:
ivan@155: %       x - sparse solution
ivan@155: %       cost - Objective cost
ivan@155: 
aris@219: %
ivan@155: %   Centre for Digital Music, Queen Mary, University of London.
ivan@155: %   This file copyright 2011 Ivan Damnjanovic.
ivan@155: %
ivan@155: %   This program is free software; you can redistribute it and/or
ivan@155: %   modify it under the terms of the GNU General Public License as
ivan@155: %   published by the Free Software Foundation; either version 2 of the
ivan@155: %   License, or (at your option) any later version.  See the file
ivan@155: %   COPYING included with this distribution for more information.
ivan@155: %   
ivan@155: %%
ivan@155: 
ivan@155: % Initial guess for the coefficients
ivan@155: 
ivan@155: if (isfield(param, 'initcoeff'))
ivan@155:    initX = param.initcoeff;
ivan@155: else
ivan@155:    initX = zeros(size(A,2),size(b,2));
ivan@155: end
ivan@155: 
ivan@155: % to - 1/(step size) . It is larger than spectral norm of dictionary A
ivan@155: 
ivan@155: if isfield(param, 'to')
ivan@155:    to = param.to;
ivan@155: else
ivan@161:    to = .1+(svds(A,1))^2;
ivan@155: end
ivan@155: 
ivan@155: % lambda - Lagrangian multiplier. (regulates shrinkage)
ivan@155: 
ivan@155: if isfield(param, 'lambda')
ivan@155:     lambda = param.lambda;
ivan@155: else
ivan@155:     lambda = 2*.2; 
ivan@155: end
ivan@155: 
ivan@155: % Inner-loop maximum iteration number.
ivan@155: 
ivan@155: if isfield(param, 'iternum')
ivan@155:     maxIT = param.iternum;
ivan@155: else
ivan@155:     maxIT = 1000; 
ivan@155: end
ivan@155: 
ivan@155: % Stopping criterion for iterative softthresholding
ivan@155: 
ivan@155: if isfield(param, 'epsilon')
ivan@155:     epsilon = param.epsilon;
ivan@155: else
ivan@155:     epsilon = 1e-7; 
ivan@155: end
ivan@155: 
ivan@155: % Debiasing. 0 = No, 1 = Yes
ivan@155: 
ivan@155: if isfield(param, 'map')
ivan@155:     map = param.map;
ivan@155: else
ivan@161:     map = 0; 
ivan@155: end
ivan@155: 
ivan@155: 
ivan@155: [X, cost] = mm1(A,b,initX,to,lambda,maxIT,epsilon,map); 
ivan@155: cost
ivan@155: end