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Proceedings of the Institute for System Programming of the RAS, 2022, Volume 34, Issue 2, Pages 135–144
DOI: https://doi.org/10.15514/ISPRAS-2022-34(2)-11
(Mi tisp683)
 

Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks

P. P. Shibaev, A. A. Chupakhin

Lomonosov Moscow State University
Abstract: Using Received Signal Strength Indicator (RSSI) values to detect human presence is a well-known Wi-Fi sensing technique. In this paper, an overview of existing algorithms solving the problem is considered. Two new techniques based on the discrete Kolmogorov-Wiener filter and the gated recurrent unit neural network are proposed. Human detection experiment results are presented along with algorithms' accuracy analysis.
Keywords: Wi-Fi-sensing, human detection, Kolmogorov-Wiener filter, gated recurrent neural network
Document Type: Article
Language: English
Citation: P. P. Shibaev, A. A. Chupakhin, “Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks”, Proceedings of ISP RAS, 34:2 (2022), 135–144
Citation in format AMSBIB
\Bibitem{ShiChu22}
\by P.~P.~Shibaev, A.~A.~Chupakhin
\paper Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks
\jour Proceedings of ISP RAS
\yr 2022
\vol 34
\issue 2
\pages 135--144
\mathnet{http://mi.mathnet.ru/tisp683}
\crossref{https://doi.org/10.15514/ISPRAS-2022-34(2)-11}
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