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Modelli Mistura e Algoritmo EM

Abstract

Bibliografia 107

References (75)

  1. * size(L,1)) 28 error('stats:gmdistribution:wdensity:IllCondCov', ...
  2. 'Ill-conditioned covariance created');
  3. 30 end 31 logDetSigma = 2 * sum(log(diagL));
  4. else % le matrici sono diagonali
  5. L = sqrt(Sigma(:,:,j));
  6. 34 if any(L) < eps(max(L)) * d 35 error('stats:gmdistribution:wdensity:IllCondCov', ...
  7. 'Ill-conditioned covariance created.') 37 end 38 logDetSigma = sum( log(Sigma(:,:,
  8. Xcentered = bsxfun(@minus, X, mu(j,:));
  9. if CovType == 2 % le matrici non sono diagonali 43 xRinv = Xcentered /L ; 44 else % le matrici sono diagonali 45 xRinv = bsxfun(@times, Xcentered , (1./ L));
  10. 46 end 47 mahalaD(:,j) = sum(xRinv.^2, 2);
  11. 48 {log_lh(:,j) = -0.5 * mahalaD(:,j) +(-0.5 * logDetSigma + 49 log_prior(j)) -d * log(2 * pi)/2
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