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It is demonstrated by the experiments that the proposed algorithm can make model selection automatically during the parameter estimation, with the mixing proportions of the extra Gaussians attenuating to zero. As compared with the BYY automated model selection algorithms, it converges more stably and accurately as the number of samples becomes large.<\/jats:p>","DOI":"10.1142\/s0218001404003812","type":"journal-article","created":{"date-parts":[[2005,1,3]],"date-time":"2005-01-03T11:23:51Z","timestamp":1104751431000},"page":"1501-1512","source":"Crossref","is-referenced-by-count":18,"title":["ENTROPY PENALIZED AUTOMATED MODEL SELECTION ON GAUSSIAN MIXTURE"],"prefix":"10.1142","volume":"18","author":[{"given":"JINWEN","family":"MA","sequence":"first","affiliation":[{"name":"Department of Information Science, School of Mathematical Sciences &amp; LMAM, Peking University, Beijing, 100871, P. R. 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