JIEIE
Journal of the Korean Institute of Illuminating
and Electrical Installation Engineers
KIIEE
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ISSN : 1229-4691 (Print)
ISSN : 2287-5034 (Online)
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Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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J Korean Inst. IIIum. Electr. Install. Eng.
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2022-02
(Vol.36 No.02)
10.5207/JIEIE.2022.36.2.014
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References
1
Kim Soo-jung, 2020, A Case Study by Type of Experience Marketing Based on Data Intelligence(DI), Cdak Socierty of Communication Design
2
Lim Jae-Wook, 2021, TOA Based Indoor Positioning Algorithm in NLOS Environments, The Institute of Positioning, Navigation, and Timing, Vol. 10, pp. 121-130
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Kim Min-jeong, 2013, Positioning Estimator Design of the Smart per on Tablet Model Using RSSI, Ph.D. Dissertations
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Yan J., 2018, Hybrid Kernel Based Machine Learning Using Received Signal Strength Measurements for Indoor Localization, IEEE Trans. Veh. Technol., Vol. 67, No. 3, pp. 2824-2829
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Carotenuto R., Merenda M., Iero D., Corte F. G. D., 2019, An Indoor Ultrasonic System for Autonomous 3-D Positioning, IEEE Trans. Instrum. Meas., Vol. 68, No. 7, pp. 2507-2518
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Subhan F., Hasbullah H., Ashraf K., 2013, Kalman Filter-based Hybrid Indoor Position Estimation Technique in Bluetooth Networks, Int. J. Nav. Observ., Vol. 2013, pp. 1-14
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Lipkap M., Sippel E., Vossiek M., 2019, An Extended Kalman Filter for Direct, Real-time, Phase-based High Precision Indoor Localization, IEEE Access, Vol. 7, pp. 25288-25297
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Faragher R., 2012, Understanding the Basis of the Kalman Filter via a Simple and Intuitive Derivation, Lecture Notes, IEEE Signal Processing Magazine, Vol. 29, No. 5, pp. 128-132
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Staudemeyer Ralf C., Morris Eric Rothstein, 2019, Understanding LSTM - A Tutorial Into Long Short-Term Memory Recurrent Neural Networks, arXiv
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Hoang M. T., 2019, Recurrent Neural Networks for Accurate RSSI Indoor Localization, IEEE Internet Things J., Vol. 6, No. 6, pp. 10639-10651
