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view m-toolbox/classes/+utils/@math/loglikelihood.m @ 36:5eb86f6881ef database-connection-manager
Remove commented-out code
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % Compute log-likelihood % % M Nofrarias 15-06-09 % % $Id: loglikelihood.m,v 1.2 2011/03/24 19:59:50 ingo Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function loglk = loglikelihood(xn,in,out,noise,model,params) % parameters fs = noise(1).fs; N = length(noise(1).y); if numel(in) == 1 % 1 input / 1 output case f = in(1).x; % evaluate models eval = model(1).setParams(params,xn); h11 = double(eval); % spectra to variance C11 = (N*fs/2)*noise(1).y; % compute elements of inverse cross-spectrum matrix InvS11 = 1./C11; % compute log-likelihood terms first, all at once does not cancel the % imag part when multiplying x.*conj(x) v1v1 = conj(out(1).y - h11.*in(1).y).*(out(1).y - h11.*in(1).y); loglk = sum(InvS11.*v1v1); elseif numel(in) == 2 if(numel(out) == 1) % 2 input / 1 output case f = in(1).x; % evaluate models h11 = model(1).setParams(params,xn).double; h12 = model(2).setParams(params,xn).double; % spectra to variance C11 = (N*fs/2)*noise(1).y; % compute elements of inverse cross-spectrum matrix InvS11 = 1./C11; % compute log-likelihood terms first, all at once does not cancel the % imag part when multiplying x.*conj(x) in1 = in(1).data.getY; f = in(1).data.getX; in2 = in(2).data.getY; out1 = out(1).data.getY; v1v1 = conj(out1 - h11.*in1 - h12.*in2).*(out1 - h11.*in1 - h12.*in2); loglk = sum(InvS11.*v1v1); elseif(numel(out) == 2) % 2 input / 2 output case f = in(1).x; % evaluate models h11 = model(1).setParams(params,xn).double; h12 = model(2).setParams(params,xn).double; h21 = model(3).setParams(params,xn).double; h22 = model(4).setParams(params,xn).double; % spectra to variance C11 = (N*fs/2)*noise(1).y; C22 = (N*fs/2)*noise(2).y; C12 = (N*fs/2)*noise(3).y; C21 = (N*fs/2)*noise(4).y; % compute elements of inverse cross-spectrum matrix InvS11 = (C22./(C11.*C22 - C12.*C21)); InvS22 = (C11./(C11.*C22 - C12.*C21)); InvS12 = (C21./(C11.*C22 - C12.*C21)); InvS21 = (C12./(C11.*C22 - C12.*C21)); % compute log-likelihood terms first, all at once does not cancel the % imag part when multiplying x.*conj(x) in1 = in(1).data.getY; in2 = in(2).data.getY; out1 = out(1).data.getY; out2 = out(2).data.getY; v1v1 = conj(out1 - h11.*in1 - h12.*in2).*(out1 - h11.*in1 - h12.*in2); v2v2 = conj(out2 - h21.*in1 - h22.*in2).*(out2 - h21.*in1 - h22.*in2); v1v2 = conj(out1 - h11.*in1 - h12.*in2).*(out2 - h21.*in1 - h22.*in2); v2v1 = conj(out2 - h21.*in1 - h22.*in2).*(out1 - h11.*in1 - h12.*in2); loglk = sum(InvS11.*v1v1 + InvS22.*v2v2 - InvS12.*v1v2 - InvS21.*v2v1); end end end