0462164 20240111140923.520160905235959.9 Praha ÚTIA AV ČR 2016 59 s. E Research Report 2355 mixture-based classification data-dependent pointer recurisive mixture estimation cav_un_auth*0330517 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Likhonina Raissa UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0108105 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Suzdaleva Evgenia UTIA-B RU Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101167 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Nagy Ivan UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2016/ZS/suzdaleva-0462164.pdf cav_un_auth*0321440 GA15-03564S GA ČR The presented report is devoted to the analysis of a data-dependent pointer model, whether it brings some advantages in comparison with a data-independent pointer model at simulation and estimation of components referring to different types of distribution, including categorical, uniform, exponential and state-space components for a dynamic data-dependent model, and normal components for a static data-dependent pointer model. BB 2017 3 4 O 4o 20231122141834.1 RVO:67985556 http://hdl.handle.net/11104/0262264 S 2016 Soubory v repozitáři: 0462164.pdf 2016 Praha ÚTIA AV ČR pdf