# ITE / code / IPA / optimization / cost_Irecursive.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 30``` ```function [cost] = cost_Irecursive(Y,ds,co) %Computes the cost (cost) of signal Y given the subspace dimensions (ds) and a cost object (co); in case of cost_type='I_recursive' ISA formulation. % %INPUT: % Y: Y(:,t) is the t^th sample. % %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 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 . cum_ds = cumsum([1;ds(1:end-1)]);%1,d_1+1,d_1+d_2+1,...,d_1+...+d_{M-1}+1 = starting indices of the subspaces (M=number of subspaces). D = sum(ds); num_of_comps = length(ds); cost = 0; for m = 1 : num_of_comps-1 %cost = cost + I(y^m,[y^{m+1},...,y^M]): idx_m = [cum_ds(m) : cum_ds(m)+ds(m)-1]; idx_tail = [cum_ds(m)+ds(m) : D]; cost = cost + I_estimation(Y([idx_m,idx_tail],:),[ds(m);length(idx_tail)],co); end ```