 function [e_hat,W_hat] = estimate_ICA(x,ICA,dim_reduction)
%Performs ICA on signal x.
%
%INPUT:
% x: x(:,t) is the t^th sample.
% ICA: the method to perform independent component analysis. Possibilities:
% 1)ICA.opt_type = 'fastICA'.
% 2)ICA.opt_type = 'EASI'.
% dim_reduction: <=dim(x)[= size(x,1)]; in case of '<', dimension reduction is also carried out.
%OUTPUT:
% e_hat: estimated ICA elements; e_hat(:,t) is the t^th sample.
% W_hat: estimated ICA demixing matrix.
%
%Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "szzoli (at) cs (dot) elte (dot) hu")
%
%This file is part of the ITE (Information Theoretical Estimators) Matlab/Octave toolbox.
%
%ITE 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 software 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 ITE. If not, see <http://www.gnu.org/licenses/>.
disp('ICA estimation: started.');
switch ICA.opt_type
case 'fastICA'
%whitening:
%1)If (i) e is white and (ii) A is orthogonal, then this step can be discarded.
%2)Alternative: perform whitening in ICA directly. It is often
%advantageous to carry out whitening separately since it reduces the number
%of parameters to be optimized (approximately) to the half. [A dxd sized 'W' demixing matrix has d^2 parameters, a dxd sized ortogonal matrix can be described by only dx(d+1)/2 parameters.]
[x,W_whiten] = whiten(x,dim_reduction);
[e_hat,A_ICA,W_ICA] = fastica(x, 'whiteSig',x,'whiteMat',eye(dim_reduction),'dewhiteMat',eye(dim_reduction), ...
'approach', 'symm', 'g', 'tanh','displayMode', 'off','verbose','off', ...
'stabilization','on','maxNumIterations',3000);
W_hat = W_ICA * W_whiten;
case 'EASI'
[e_hat,W_hat] = estimate_ICA_EASI(x,dim_reduction);
otherwise
error('ICA method=?');
end
disp('ICA estimation: ready.');
