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- W2891133681 abstract "In this paper, a specific type of incomplete data in Wi-Fi fingerprinting based indoor positioning systems (WF-IPS) is presented: censored and dropped mixture data. For fitting this type of data, a censored and dropped Gaussian Mixture Model (CD-GMM) was proposed. Further, an extended version of the Expectation–Maximization (EM) algorithm is developed for estimating parameters of this model. Simulation results show the advantage of our proposal compared to existing methods. Thus, this approach not only has potential for the WF-IPSs, but also for other applications." @default.
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- W2891133681 date "2019-06-01" @default.
- W2891133681 modified "2023-10-14" @default.
- W2891133681 title "An EM algorithm for GMM parameter estimation in the presence of censored and dropped data with potential application for indoor positioning" @default.
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- W2891133681 doi "https://doi.org/10.1016/j.icte.2018.08.001" @default.
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