ITE / code / H_I_D / meta_estimators / HRPensemble_estimation.m

function [H] = HRPensemble_estimation(Y,co)
%Estimates entropy (H) from the average of H estimations on RP-ed (random projection) groups of samples; this a "meta" method, the applied H estimator can be arbitrary.
%We make use of the naming convention 'H<name>_estimation', to ease embedding new entropy estimation methods.
%   Y: Y(:,t) is the t^th sample.
%  co: entropy estimator object.
%	Zoltán Szabó, András Lőrincz: Fast Parallel Estimation of High Dimensional Information Theoretical Quantities with Low Dimensional Random Projection Ensembles. ICA 2009, pages 146-153.
%Copyright (C) 2012 Zoltan Szabo ("", "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 <>.

    g = co.group_size;    
    [d,num_of_samples] = size(Y);
	d_RP = co.dim_RP;
    num_of_groups = floor(num_of_samples/g);
H = 0;    
for k = 1 : num_of_groups
	R = randn(d_RP,d) / sqrt(d_RP);
    H = H + H_estimation(R*Y(:,(k-1)*g+1:k*g),co.member_co);
H = H / num_of_groups;
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