Factorized EM Algorithm for Mixture Estimation
A classical version of the EM algorithm is considered in the paper. Its numerical properties are improved using factorized algorithms for maximization in M step of the algorithm. The results are illustrated on simulated examples.
KeywordsMixture Model Numerical Property Normal Mixture Factorize Algorithm Radial Basis Neural Network
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- A.P. Dempster, N.M. Lair, and D.B. Rubin, “Maximum-likelihood from incomplete data via the em algorithm”, J.Royal Statist. Soc. Ser. B., vol. 39, 1977.Google Scholar
- R. Redner and H. Walker, “Mixture densities, maximum likelihood and the em algorithm”, SIAM Review, vol. 26, 1984.Google Scholar
- V. Peterka, “Bayesian approach to system identification”, in Trends and Progress in System Identification, P. Eykhoff, Ed., pp. 239–304. Pergamoll Press, Oxford, 1981.Google Scholar