0491347 20240103220248.220180724235959.9 85049369508 10.1007/978-3-319-78931-6_3 193 21 s. P cav_un_epca*0491346978-3-319-78930-929-49ChamSpringer2019HadjiskiM.AtanassovK. mixture initialisation mixture estimation prior data analysis cav_un_auth*0108105 Suzdaleva Evgenia UTIA-B Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing RU Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101167 Nagy Ivan UTIA-B Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2018/ZS/suzdaleva-0491347.pdf cav_un_auth*0321440 GA15-03564S GA ČR The initialization is known to be a critical task for running a mixture estimation algorithm. A majority of approaches existing in the literature are related to initialization of the expectation-maximization algorithm widely used in this area. This study focuses on the initialization of the recursive mixture estimation for the case of normal components, where the mentioned methods are not applicable. Its key part is a choice of the initial statistics of normal components. BB 10000 10100 10103 2020 2 RVO:67985556 http://hdl.handle.net/11104/0285513 S 2019 85049369508 SCOPUS PUBMED WOS cav_un_epca*0491346 Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications Springer 2019 Cham 29 49 978-3-319-78930-9 Studies in Computational Intelligence 757 340 Hadjiski M. 340 Atanassov K.