0448117 20240111140908.020151119235959.9 84957604223 000380403500025 10.1109/IDAACS.2015.7340715 Recursive Estimation of Mixtures of Exponential and Normal Distributions 6 s. C cav_un_epca*0448116978-1-4673-8361-5Proceedings of the 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)137-142PiscatawayIEEE2015 recursive mixture estimation mixture of different distributions dynamic switching model exponential distribution cav_un_auth*0108105 Zpracování signálů Department of Signal Processing ZS ZS Department of Signal Processing Suzdaleva Evgenia UTIA-B 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. cav_un_auth*0274528 Zpracování signálů Department of Signal Processing ZS ZS Mlynářová Tereza UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2015/ZS/suzdaleva-0448117.pdf cav_un_auth*0308433 7H14005 GA MŠk BE cav_un_auth*0306850 7H14004 GA MŠk cav_un_auth*0321440 GA15-03564S GA ČR CZ The paper deals with estimation of a mixture of normal and exponential distributions with the dynamic model of their switching. A separate estimation of normal or exponential mixtures is solved by various approaches in many papers over the world. However, in some application areas, data are of such a nature that they should be described by a combination of exponential and normal models. The paper proposes a recursive Bayesian algorithm of estimation of such a mixture based on continuously measured data. Specific tasks the paper solves are: (i) parameter estimation of both the types of components; (ii) parameter estimation of the dynamic switching model and (iii) detection of the currently active component. Results of experiments with real data are demonstrated. cav_un_auth*0320279 International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications /8./ (IDAACS'2015) 24.09.2015-26.09.2015 Warsaw PL BB 2016 3 PR RVO:67985556 http://hdl.handle.net/11104/0250068 S n.a. Proceedings Paper Computer Science Artificial Intelligence|Computer Science Theory Methods|Engineering Electrical Electronic 2015 84957604223 SCOPUS 000380403500025 WOS pdf cav_un_epca*0448116 Proceedings of the 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) 978-1-4673-8361-5 137 142 Piscataway IEEE 2015