# ITE / code / IPA / demos / estimate_complex_ISA.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 31 32 33 34 35 36 37 38 39 40 41 42``` ```function [e_real_hat,W_real_hat,de_real_hat,e_hat] = estimate_complex_ISA(x,ICA_method,opt_type,cost_type,cost_name,unknown_dimensions,de,dim_reduction) %Estimates the complex ISA model. Method: complex -> real transformation, +real ISA. % %INPUT: % x: x(:,t) is the observation at time t. % ICA_method: the name of the ICA method applied, see 'estimate_ICA.m'. % cost_type, cost_name, opt_type: cost type, cost name, optimization type. Example: cost_type = 'sumH', cost_name = 'Renyi_kNN_1tok', opt_type = 'greedy' means that we use an entropy sum ISA formulation ('sumH'), where the entropies are estimated Renyi entropies via kNN methods ('Renyi_kNN_1tok') and the optimization is greedy; see also 'demo_ISA.m' % unknown_dimensions: '0' means 'the subspace dimensions are known'; '1' means 'the number of the subspaces are known' (but the individual dimensions are unknown). % de: % 1)in case of 'unknown_dimensions = 0': 'de' contains the subspace dimensions. % 2)in case of 'unknown_dimensions = 1': the length of 'de' must be equal to the number of subspaces, but the coordinates of the vector can be arbitrary. % dim_reduction: dim(x) = size(x,1) >= dim_reduction; if '>' holds, perform dimension reduction to dimension dim_reduction, too. %OUTPUT: % e_real_hat: e_real_hat(:,t) is the estimated (real) ISA source at time t. % W_real_hat: estimated (real) ISA demixing matrix. % de_real_hat: in case of known subspace dimensions ('unknown_dimensions = 0') de_real_hat = 2*de; else it contains the estimated (real) subspace dimensions; ordered increasingly. % e_hat: e_hat(:,t) is the estimated (complex) ISA source at time t. %REFERENCE: % Zoltan Szabo and Andras Lorincz. Complex Independent Process Analysis. Acta Cybernetica 19:177-190, 2009. % %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 . %complex -> problem real transformation (x_real,de_real,dim_reduction_real): x_real = C2R_vector(x); de_real = 2 * de; dim_reduction_real = 2 * dim_reduction; %ISA on the transformed data: [e_real_hat,W_real_hat,de_real_hat] = estimate_ISA(x_real,ICA_method,opt_type,cost_type,cost_name,unknown_dimensions,de_real,dim_reduction_real); %real->complex transformation: e_hat = R2C_vector(e_real_hat); ```
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