# ITE / code / H_I_D / meta_estimators / HShannon_DKL_U_initialization.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 29 function [co] = HShannon_DKL_U_initialization(mult) %Initialization of the "meta" Shannon entropy estimator defined according to the relation H(Y) = -D(Y',U) + log(\prod_i(b_i-a_i)), where y\in[a,b] = \times_{i=1}^d[a_i,b_i], D is the Kullback-Leibler divergence, Y' = linearly transformed version of Y to [0,1]^d, and U is the uniform distribution on [0,1]^d. % %Note: % 1)The estimator is treated as a cost object (co). % 2)We make use of the naming convention 'H_initialization', to ease embedding new entropy estimation methods. % %INPUT: % mult: is a multiplicative constant relevant (needed) in the estimation; '=1' means yes, '=0' no. % %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 . %mandatory fields: co.name = 'Shannon_DKL_U'; co.mult = mult; %other fields: co.member_name = 'KL_kNN_k'; %you can change it to any Kullback-Leibler divergence estimator co.member_co = D_initialization(co.member_name,mult); 
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