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Neural Network Signal Processing of a Quasi-Distributed Fiber-Optic Measuring Network with Amplitude Sensors

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Bulletin of the Russian Academy of Sciences: Physics Aims and scope

Abstract

he possibility of neural network signal processing of a tomography quasi-distributed fiber-optic measuring network is shown. The measuring network presents several nonlinear measuring lines with fiber-optical amplitude sensing elements. The data processing is carried out by a neural network containing an inner layer of nonlinear neurons. As a result, the distribution function of the measuring physical field is reconstructed. The results of numerical experiments, as well as experiments with the layout of a measuring network of dimension 8 × 8, are presented.

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Funding

The presented study is performed within the state task of the Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Sciences (project no. 121021600267-6).

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Authors and Affiliations

  1. Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Sciences, 690041, Vladivostok, Russia

    O. T. Kamenev & Yu. S. Petrov

  2. Far Eastern Federal University, 690041, Vladivostok, Russia

    A. O. Kamenev

Authors
  1. O. T. Kamenev
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  2. A. O. Kamenev
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  3. Yu. S. Petrov
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Correspondence to O. T. Kamenev.

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Kamenev, O.T., Kamenev, A.O. & Petrov, Y.S. Neural Network Signal Processing of a Quasi-Distributed Fiber-Optic Measuring Network with Amplitude Sensors. Bull. Russ. Acad. Sci. Phys. 87 (Suppl 3), S398–S401 (2023). https://doi.org/10.1134/S1062873823705937

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  • DOI: https://doi.org/10.1134/S1062873823705937

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