Paper Info
Title
Model Selection Criterion for Multivariate Bounded Asymmetric Gaussian Mixture Model
Abstract
In this paper, model selection criterion for bounded support asymmetric Gaussian mixture model (BAGMM) using minimum message length (MML) is proposed. The proposed approach is validated using synthetic data, real data and occupancy detection application. The proposed approach is compared with other state of the art model selection approaches. Moreover, the developed bounded mixture is compared with asymmetric Gaussian mixture model (AGMM).
Year
DOI
Venue
2021
10.23919/EUSIPCO54536.2021.9616056
29TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2021)
Keywords
DocType
ISSN
Multivariate Bounded Asymmetric Gaussian Mixture Model (BAGMM), Minimum Message Length (MML), Model Selection, Data Clustering, Occupancy Detection
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Zixiang Xian100.34
Muhammad Azam225.76
Manar Amayri304.39
Nizar Bouguila41539146.09