최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Sensors, v.19 no.19, 2019년, pp.4229 -
Cwalina, Krzysztof K. (Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland) , Rajchowski, Piotr (Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland) , Blaszkiewicz, Olga (Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland) , Olejniczak, Alicja (Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland) , Sadowski, Jaroslaw (Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland)
In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with com...
10.3390/app8071209 Cwalina, K.K., Ambroziak, S.J., Rajchowski, P., Sadowski, J., and Stefanski, J. (2018). A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks. Appl. Sci., 8.
Rajchowski, P. (2017). Research and Analysis Precision of Position Estimation of Moving Object in Hybrid Localization System. [Ph.D. Thesis, Gdansk University of Technology]. (In polish).
DecaWave (2016). DWM1000 User Manual, Ver. 2.07, DecaWave.
10.1109/ICARCV.2018.8581305 Krishnan, S., Mendoza Santos, R.X., Yap, E.R., and Zin, M.T. (2018, January 18-21). Improving UWB Based Indoor Positioning in Industrial Environments through Machine Learning. Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore.
Marano NLOS Identification and Mitigation for Lozalization Based on UWB Experimental Data IEEE J. Sel. Areas Commun. 2010 10.1109/JSAC.2010.100907 28 1026
10.1109/COMST.2018.2846401 Mao, Q., Hu, F., and Hao, Q. (2018). Deep Learning for Intelligent Wireless Networks: A Comprehensive Survey. IEEE Commun. Surv. Tutor., 20.
10.1109/COMST.2019.2904897 Zhang, C., Patras, P., and Haddadi, H. (2019). Deep Learning in Mobile and Wireless Networking: A Survey. IEEE Commun. Surv. Tutor., 21.
Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, Massachusetts Institute of Technology/The MIT Press.
Tabaa NLOS Identification for UWB Body Communications Int. J. Comput. Appl. 2015 124 12
Groves, P.D., Jiang, Z., Wang, L., and Ziebart, M.K. (2012, January 17-21). Intelligent Urban Positioning using Multi-Constellation GNSS with 3D Mapping and NLOS Signal Detection. Proceedings of the 25th International Technical Meeting of the Satellite Division of the Institute of Navigation (Ion Gnss 2012), Nashville, TN, USA.
10.1145/2834892.2834896 Young, S.R., Rose, D.C., Karnowski, T.P., Lim, S.-H., and Patton, R.M. (2015, January 15). Optimizing deep learning hyper-parameters through an evolutionary algorithm. Proceedings of the MLHPC ‘15 Workshop on Machine Learning in High-Performance Computing Environments, Austin, TX, USA.
Bergstra Random Search for Hyper-Parameter Optimization J. Mach. Learn. Res. 2012 13 281
Patterson, J., and Gibson, A. (2017). Deep Learning: A Practitioner’s Approach, O’Reilly Media, Inc.
Ferreira A high bit resolution FPGA implementation of a FNN with a new algorithm for the activation function Neurocomputing 2007 10.1016/j.neucom.2006.11.028 71 71
Kingma, D.P., and Ba, J.L. (2015, January 7-9). Adam: Method for Stochastic Optimization. Proceedings of the 3rd International Conference on Learning Representations (ICLR), San Diego, CA, USA.
10.23919/URSIGASS.2017.8104968 Cwalina, K.K., Ambroziak, S.J., Rajchowski, P., and Correia, L.M. (2017, January 19-26). Radio channel measurements in 868 MHz off-body communications in a ferry environment. Proceedings of the XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), Montreal, QC, Canada.
10.3390/app8060988 Cwalina, K.K., Ambroziak, S.J., and Rajchowski, P. (2018). An Off-Body Narrowband and Ultra-Wide Band Channel Model for Body Area Networks in a Ferryboat Environment. Appl. Sci., 8.
Ambroziak An Off-Body Channel Model for Body Area Networks in Indoor Environments IEEE Trans. Antennas Propag. 2016 10.1109/TAP.2016.2586510 64 4022
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.