0364544 20240111140800.420110927235959.9 5 s. CD cav_un_epca*0364556978-1-4577-1424-5527-531PiscatawayIEEE2011 mixture models hidden Markov models state estimation online estimation cav_un_auth*0213012 Nagy I. CZ cav_un_auth*0108105 Suzdaleva Evgenia Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Signal Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0274528 Mlynářová Tereza Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2011/AS/nagy-comparison of state estimation using finite mixtures and hidden markov models.pdf 1M0572 GA MŠk cav_un_auth*0001814 TA01030123 GA TA ČR cav_un_auth*0271776 CEZ:AV0Z10750506 Many various algorithms are developed for state estimation of dynamic switching systems. It is not a straightforward task to choose the most suitable one. This paper deals with testing of state estimation via two wellknown approaches: recursive estimation with finite mixtures and iterative technique with hidden Markov models. A discussion of comparison of these online and offline counterparts is of true interest. The paper describes experiments providing a comparison of these methods. cav_un_auth*0274520 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications Prague 15.09.2011-17.09.2011 CZ 2012 BC 3 http://hdl.handle.net/11104/0200007 2011 pdf cav_un_epca*0364556 Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems : Technology and Application 978-1-4577-1424-5 527 531 Piscataway IEEE 2011