function [co] = DJdistance_initialization(mult)
%Initialization of the symmetrised Kullback-Leibler, also called J-distance divergence estimator, defined according to the relation:
%D_J(f_1,f_2) = D(f_1,f_2)+D(f_2,f_1), where D denotes the Kullback-Leibler divergence.
%
%Note:
% 1)The estimator is treated as a cost object (co).
% 2)We make use of the naming convention 'D<name>_initialization', to ease embedding new divergence estimation methods.
%
%INPUT:
% mult: is a multiplicative constant relevant (needed) in the estimation; '=1' means yes, '=0' no.
%OUTPUT:
% co: cost object (structure).
%
%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/>.
%mandatory fields:
co.name = 'Jdistance';
co.mult = mult;
%other fields:
co.member_name = 'Renyi_kNN_k'; %you can change it to any Kullback-Leibler entropy estimator, the Renyi divergence converges to the Shannon's as \alpha->1.
co.member_co = D_initialization(co.member_name,mult);