Suchergebnisse - "generalized expectation maximization algorithm"

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  1. 1

    Multiple testing for neuroimaging via hidden Markov random field von Shu, Hai, Nan, Bin, Koeppe, Robert

    ISSN: 0006-341X, 1541-0420
    Veröffentlicht: England Blackwell Publishing Ltd 01.09.2015
    Veröffentlicht in Biometrics (01.09.2015)
    “… Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and …”
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  2. 2

    Research on Multi-Parameter Optimization of Indoor WiFi Positioning Technology von WANG Yingying, CHANG Jun, WU Hao

    ISSN: 1000-3428
    Veröffentlicht: Editorial Office of Computer Engineering 01.09.2021
    Veröffentlicht in Ji suan ji gong cheng (01.09.2021)
    “… The existing WiFi-based indoor positioning technology is affected by the number of antennas and channel bandwidth, and has the problems of low positioning …”
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  3. 3

    Generalized expectation–maximization approach to LPV process identification with randomly missing output data von Yang, Xianqiang, Huang, Biao, Zhao, Yujia, Lu, Yaojie, Xiong, Weili, Gao, Huijun

    ISSN: 0169-7439, 1873-3239
    Veröffentlicht: Elsevier B.V 15.11.2015
    Veröffentlicht in Chemometrics and intelligent laboratory systems (15.11.2015)
    “… This paper considers parameter estimation for linear parameter varying (LPV) systems with randomly missing output data. The multi-model LPV model is adopted …”
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  4. 4

    Asynchronous Linear Modulation Classification With Multiple Sensors via Generalized EM Algorithm von Ozdemir, Onur, Wimalajeewa, Thakshila, Dulek, Berkan, Varshney, Pramod K., Wei Su

    ISSN: 1536-1276, 1558-2248
    Veröffentlicht: New York IEEE 01.11.2015
    Veröffentlicht in IEEE transactions on wireless communications (01.11.2015)
    “… In this paper, we consider the problem of automatic modulation classification with multiple sensors in the presence of unknown time offset, phase offset and …”
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  5. 5

    Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models von Fung, Tsz Chai

    ISSN: 0167-6687, 1873-5959
    Veröffentlicht: Elsevier B.V 01.11.2022
    Veröffentlicht in Insurance, mathematics & economics (01.11.2022)
    “… Insurance claim severity data are characterized by complex distributional phenomenons, where flexible density estimation tools such as the finite mixture …”
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  6. 6

    Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions von Dang, Utkarsh J., Gallaugher, Michael P.B., Browne, Ryan P., McNicholas, Paul D.

    ISSN: 0176-4268, 1432-1343
    Veröffentlicht: New York Springer US 01.04.2023
    Veröffentlicht in Journal of classification (01.04.2023)
    “… Families of mixtures of multivariate power exponential (MPE) distributions have already been introduced and shown to be competitive for cluster analysis in …”
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  7. 7

    Self-tuning robust adjustment within multivariate regression time series models with vector-autoregressive random errors von Kargoll, Boris, Kermarrec, Gaël, Korte, Johannes, Alkhatib, Hamza

    ISSN: 0949-7714, 1432-1394
    Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2020
    Veröffentlicht in Journal of geodesy (01.05.2020)
    “… The iteratively reweighted least-squares approach to self-tuning robust adjustment of parameters in linear regression models with autoregressive (AR) and …”
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  8. 8

    Deep GEM-Based Network for Weakly Supervised UWB Ranging Error Mitigation von Li, Yuxiao, Mazuelas, Santiago, Shen, Yuan

    ISSN: 2155-7586
    Veröffentlicht: IEEE 29.11.2021
    Veröffentlicht in MILCOM IEEE Military Communications Conference (29.11.2021)
    “… Ultra-wideband (UWB)-based techniques, while becoming mainstream approaches for high-accurate positioning, tend to be challenged by ranging bias in harsh …”
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  9. 9

    Underdetermined Convolutive Source Separation Using GEM-MU With Variational Approximated Optimum Model Order NMF2D von Al-Tmeme, Ahmed, Woo, Wai Lok, Dlay, Satnam Singh, Gao, Bin

    ISSN: 2329-9290, 2329-9304
    Veröffentlicht: Piscataway IEEE 01.01.2017
    “… An unsupervised machine learning algorithm based on nonnegative matrix factor Two-dimensional deconvolution (NMF2D) with approximated optimum model order is …”
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  10. 10

    Distributed asynchronous modulation classification based on hybrid maximum likelihood approach von Wimalajeewa, Thakshila, Jagannath, Jithin, Varshney, Pramod K., Drozd, Andrew, Wei Su

    Veröffentlicht: IEEE 01.10.2015
    “… In this paper, we consider the problem of automatic modulation classification (AMC) with multiple sensors. A distributed hybrid maximum likelihood (HML) based …”
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  11. 11

    Hammerstein System Identification with Skewed and Asymmetric Noise von Wang, Chen, Liu, Xin

    ISSN: 2577-1647
    Veröffentlicht: IEEE 16.10.2023
    “… To eliminate the negative effect brought by the skewed and asymmetric measurement noise, this paper proposes a robust identification algorithm for the …”
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  12. 12

    Channel Parameter Extraction Based on BP-Neural Network in NLOS Environment von Hu, Zhexin, Bu, Fanliang, Ding, Dandan

    ISSN: 2770-663X
    Veröffentlicht: IEEE 23.09.2022
    “… The extraction of wireless channel parameters is important for channel modeling and wireless resource scheduling in complex environments. Based on QuaDriGa …”
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  13. 13

    Joint Channel Estimation, Interference Cancellation, and Data Detection for Ambient Backscatter Communications von Darsena, Donatella, Gelli, Giacinto, Verde, Francesco

    ISSN: 1948-3252
    Veröffentlicht: IEEE 01.06.2018
    “… This paper deals with the problem of joint channel estimation, interference suppression, and data detection for ambient backscatter communications, where a …”
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  14. 14

    Robust global identification of linear parameter varying systems with generalised expectation–maximisation algorithm von Yang, Xianqiang, Lu, Yaojie, Yan, Zhibin

    ISSN: 1751-8644, 1751-8652
    Veröffentlicht: The Institution of Engineering and Technology 23.04.2015
    Veröffentlicht in IET control theory & applications (23.04.2015)
    “… In this study, a robust approach to global identification of linear parameter varying (LPV) systems in an input–output setting is proposed. In practice, the …”
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