0462336 20240111140923.820160908235959.9 85006049361 000391554300037 10.1109/IS.2016.7737431 7 s. C cav_un_epca*0462335978-1-5090-1353-1265-271SofiaIEEE2016 mixture-based clustering recursive mixture estimation mixture of uniform distributions data-dependent pointer 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*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*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/2016/ZS/suzdaleva-0462336.pdf cav_un_auth*0321440 GA15-03564S GA ČR This paper deals with clustering non-gaussian data with fixed bounds. It considers the problem using recursive mixture estimation algorithms under the Bayesian methodology. Such a solution is often desired in areas, where the assumption of normality of modeled data is rather questionable and brings a series of limitations (e.g., non-negative, bounded data, etc.). Here for modeling the data a mixture of uniform distributions is taken, where individual clusters are described by mixture components. For the on-line detection of clusters of measured bounded data, the paper proposes a mixture estimation algorithm based on (i) the update of reproducible statistics of uniform components; (ii) the heuristic initialization via the method of moments; (iii) the non-trivial adaptive forgetting technique; (iv) the data-dependent dynamic pointer model. The approach is validated using realistic traffic flow simulations. cav_un_auth*0333078 2016 IEEE 8th International Conference on Intelligent Systems IS'2016 04.09.2016-06.09.2016 Sofia BG BB 2017 3 PR RVO:67985556 http://hdl.handle.net/11104/0262262 S n.a. Proceedings Paper Computer Science Artificial Intelligence|Computer Science Hardware Architecture 2016 85006049361 SCOPUS 000391554300037 WOS pdf cav_un_epca*0462335 Proceedings of 2016 IEEE 8th International Conference on Intelligent Systems 978-1-5090-1353-1 265-271 265 271 Sofia IEEE 2016