bibtype	J - Journal Article
ARLID	0410331
utime	20240903170411.9
mtime	20060210235959.9
title (primary) (eng)	Self-organizing maps and probabilistic neural networks
specification	page_count 9 s.
serial	ARLID cav_un_epca*0290321 ISSN 1210-0552 title Neural Network World volume_id 10 volume 3 (2000) page_num 407-415 publisher name Ústav informatiky AV ČR, v. v. i.
author (primary)	ARLID cav_un_auth*0101091 name1 Grim name2 Jiří institution UTIA-B full_dept Department of Pattern Recognition fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI	09K
COSATI	12B
cas_special	project project_id IAA2075703 agency GA AV country CZ ARLID cav_un_auth*0218731 project project_id VS96063 agency MŠMT country CZ ARLID cav_un_auth*0025066 project project_id KSK1075601 agency GA AV country CZ ARLID cav_un_auth*0027435 research AV0Z1075907 abstract (eng) The self-organizing map (SOM) algorithm for training of artificial neural networks is shown to be closely related to a sequential modification of EM algorithm for maximum-likelihood estimation of finite mixtures. Theestablished correspondence provides a helpful theoretical basis for interpretation of the properties of SOM algorithm and for the choice of involved parameters. RIV BB department RO permalink http://hdl.handle.net/11104/0003514 ID_orig UTIA-B 20000047 arlyear 2000 mrcbU63 cav_un_epca*0290321 Neural Network World 1210-0552 Roč. 10 č. 3 2000 407 415 Ústav informatiky AV ČR, v. v. i.