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Synthesis of the Rational Analyzing Function for Feature Extraction of Signals from the Electrostatic Location System

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High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production (HPCST 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1733))

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Abstract

The article deals with an algorithm for extracting features of an electrostatic signal from the electrostatic location system. The algorithm is based on converting a signal into a time-frequency distribution by means of convolution with analyzing function. In this article a software algorithm for the synthesis of a special function and a method for analyzing the time-frequency distribution are considered. The precision of the method for extracting features of the electrostatic signal with different signal-to-noise ratios is estimated. The precision of the method is evaluated with respect to the precision of the standard method. The standard method is based on the Morlet wavelet function as an analyzing one.

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Acknowledgements

The reported study was funded by RFBR, project number 20-37-90028.

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Authors and Affiliations

  1. MIREA – Russian Technological University, Vernadsky Avenue 78, 119454, Moscow, Russia

    Yurii Skryabin & Dmitry Potekhin

Authors
  1. Yurii Skryabin
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  2. Dmitry Potekhin
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Corresponding author

Correspondence to Yurii Skryabin .

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Editors and Affiliations

  1. Altai State University, Barnaul, Russia

    Vladimir Jordan

  2. MIREA - Russian Technological University, Moscow, Russia

    Ilya Tarasov

  3. Novosibirsk State Technical University, Novosibirsk, Russia

    Ella Shurina

  4. Lomonosov Moscow State University, Moscow, Russia

    Nikolay Filimonov

  5. Tomsk State University of Control Systems and Radio-Electronics, Tomsk, Russia

    Vladimir Faerman

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Skryabin, Y., Potekhin, D. (2023). Synthesis of the Rational Analyzing Function for Feature Extraction of Signals from the Electrostatic Location System. In: Jordan, V., Tarasov, I., Shurina, E., Filimonov, N., Faerman, V. (eds) High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production. HPCST 2022. Communications in Computer and Information Science, vol 1733. Springer, Cham. https://doi.org/10.1007/978-3-031-23744-7_19

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  • DOI: https://doi.org/10.1007/978-3-031-23744-7_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23743-0

  • Online ISBN: 978-3-031-23744-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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