ITE / code / H_I_D / utilities / compute_CDSS.m

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```function [H] = compute_CDSS(Y_sorted) %Computes the Renyi quadratic entropy (H) for the 'Renyi_CDSS' entropy estimator, see 'HRenyi_CDSS_estimation.m'. % %INPUT: % Y_sorted: vector, Y_sorted(t) is the t^th sample, Y_sorted(1)<=...<=Y_sorted(end). % %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 . num_of_samples = length(Y_sorted); m = floor(sqrt(num_of_samples));%m/num_of_samples->0, m,num_of_samples->infty H = 0; for i = 1 : num_of_samples-m for j = i+1 : i+m-1 H = H + (Y_sorted(j) - Y_sorted(i+m))^2 * (Y_sorted(j) - Y_sorted(i))^2 / (Y_sorted(i+m) - Y_sorted(i))^5; end end H = -log(30*H/(num_of_samples*(num_of_samples-m))); ```
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