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https://doi.org/10.17535/crorr.2018.0017

Cluster Detection in Noisy Environment by Using the Modified EM Algorithm

Vedran Novoselac ; Mechanical Engineering Faculty in Slavonski Brod, J. J. Strossmayer University of Osijek, Slavonski Brod, Croatia
Zlatko Pavić ; Mechanical Engineering Faculty in Slavonski Brod, J. J. Strossmayer University of Osijek, Slavonski Brod, Croatia

Puni tekst: engleski, pdf (21 MB) str. 223-234 preuzimanja: 222* citiraj
APA 6th Edition
Novoselac, V. i Pavić, Z. (2018). Cluster Detection in Noisy Environment by Using the Modified EM Algorithm. Croatian Operational Research Review, 9 (2), 223-234. https://doi.org/10.17535/crorr.2018.0017
MLA 8th Edition
Novoselac, Vedran i Zlatko Pavić. "Cluster Detection in Noisy Environment by Using the Modified EM Algorithm." Croatian Operational Research Review, vol. 9, br. 2, 2018, str. 223-234. https://doi.org/10.17535/crorr.2018.0017. Citirano 05.08.2021.
Chicago 17th Edition
Novoselac, Vedran i Zlatko Pavić. "Cluster Detection in Noisy Environment by Using the Modified EM Algorithm." Croatian Operational Research Review 9, br. 2 (2018): 223-234. https://doi.org/10.17535/crorr.2018.0017
Harvard
Novoselac, V., i Pavić, Z. (2018). 'Cluster Detection in Noisy Environment by Using the Modified EM Algorithm', Croatian Operational Research Review, 9(2), str. 223-234. https://doi.org/10.17535/crorr.2018.0017
Vancouver
Novoselac V, Pavić Z. Cluster Detection in Noisy Environment by Using the Modified EM Algorithm. Croatian Operational Research Review [Internet]. 2018 [pristupljeno 05.08.2021.];9(2):223-234. https://doi.org/10.17535/crorr.2018.0017
IEEE
V. Novoselac i Z. Pavić, "Cluster Detection in Noisy Environment by Using the Modified EM Algorithm", Croatian Operational Research Review, vol.9, br. 2, str. 223-234, 2018. [Online]. https://doi.org/10.17535/crorr.2018.0017

Sažetak
The paper studies the problem of a cluster detection in the noisy environment. The solution of this problem is based on the well known Expectation Maximization (EM) algorithm. By utilizing the Mahalanobis distance, and modifying the hidden variable, the rejection procedure is constructed so that it omits data from calculation of the current iteration step. Thus we construct the adaptive framework for solving the above problem. Several numerical examples are presented to illustrate the proposed algorithm.

Ključne riječi
clustering; EM; Mahalanobis distance; least squares; least absolute devoation; Davies-Bouldin index

Hrčak ID: 212388

URI
https://hrcak.srce.hr/212388

Posjeta: 490 *