function [co] = DsymBregman_DBregman_initialization(mult) %Initialization of the symmetric Bregman distance estimator using the relation: D_S = (D_NS(f1,f2) + D_NS (f2,f1)) / alpha, where D_NS is the nonsymmetric Bregman distance. % %Note: % 1)The estimator is treated as a cost object (co). % 2)We use the naming convention 'D<name>_initialization' to ease embedding new divergence estimation methods. % 3)This is a meta method: the (nonsymmetric) Bregman distance estimator can arbitrary. % %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 = 'symBregman_DBregman'; co.mult = mult; %other fields: co.alpha = 0.7; %assumption: not equal to 1 co.member_name = 'Bregman_kNN_k'; %you can change it to any (nonsymmetric) Bregman distance estimator co.member_co = D_initialization(co.member_name,mult); co.member_co.alpha = co.alpha; %automatism for setting the parameters (co.alpha) of member_co (co_2) in a <=2 deep meta construction (co_1 -> co_2); otherwise, please set the parameters (co.alpha) in the member_co-s.