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  1. 2025

  2. Compensation of nonlinear signal distortions in optical fiber communication systems

    Redyuk, A., Sidelnikov, O. & Fedoruk, M., Apr 2025, In: Optics Communications. 578, 131418.

    Research output: Contribution to journal › Article › peer-review

  3. 2024

  4. Оптоволоконный сенсор на брэгговских решетках для взвешивания транспортных средств в движении

    Редюк, А. А. & Иванов, С. Ю., 23 Dec 2024, Роспатент - Федеральная служба по интеллектуальной собственности, Patent No. 230853, 2 Nov 2024, Priority date 2 Nov 2024, Priority No. 2024133010

    Research output: Patent › Patent for utility model

  5. Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning

    Borozdin, P., Erushin, E., Kozmin, A., Bednyakova, A., Miroshnichenko, I., Kostyukova, N., Boyko, A. & Redyuk, A., Dec 2024, In: Sensors. 24, 23, 7518.

    Research output: Contribution to journal › Article › peer-review

  6. Compensation for Nonlinear Distortions in Optical Communication Systems Using Perturbation Theory and Multiparameter Optimization

    Redyuk, A. A., Shevelev, E. I., Danilko, V. R. & Fedoruk, M. P., Nov 2024, In: Bulletin of the Lebedev Physics Institute. 51, Suppl 6, p. S449-S457 9 p.

    Research output: Contribution to journal › Article › peer-review

  7. Wavelet-Based Machine Learning Algorithms for Photoacoustic Gas Sensing

    Kozmin, A., Erushin, E., Miroshnichenko, I., Kostyukova, N., Boyko, A. & Redyuk, A., Jun 2024, In: Optics. 5, 2, p. 207-222 16 p.

    Research output: Contribution to journal › Article › peer-review

  8. Machine Learning Methods for Compensating Signal Distortions in Fiber-Optic Communication Lines

    Sidelnikov, O. S., Redyuk, A. A. & Fedoruk, M. P., Feb 2024, In: Optoelectronics, Instrumentation and Data Processing. 60, 1, p. 1-10 10 p.

    Research output: Contribution to journal › Article › peer-review

  9. ML-Assisted Particle Swarm Optimization of a Perturbation-Based Model for Nonlinearity Compensation in Optical Transmission Systems

    Redyuk, A., Shevelev, E., Danilko, V. & Fedoruk, M., 1 Jan 2024, In: Journal of Lightwave Technology. p. 1-8

    Research output: Contribution to journal › Article › peer-review

  10. Dispersive Fourier Transform Spectrometer Based on Mode-Locked Er-Doped Fiber Laser for Ammonia Sensing

    Апрелов, Н. А., Ватник, И. Д., Харенко, Д. С. & Редюк, А. А., Jan 2024, In: Photonics. 11, 1, 45.

    Research output: Contribution to journal › Article › peer-review

  11. Interpretation models for data of metal-oxide gas sensors based on machine learning methods

    Kozmin, A. D. & Redyuk, A. A., 2024, In: Journal of Computational Technologies. 29, 4, p. 4-23 20 p.

    Research output: Contribution to journal › Article › peer-review

  12. Компенсация нелинейных искажений в системах оптической связи методами теории возмущений и многопараметрической оптимизации

    Редюк, А. А., Шевелев, Е. И., Данилко, В. Р. & Федорук, М. П., 2024, In: Квантовая электроника. 54, 3, p. 151-156 6 p., 4.

    Research output: Contribution to journal › Article › peer-review

  13. 2023

  14. Enhancing long-term stability of photoacoustic gas sensor using an extremum-seeking control algorithm

    Bednyakova, A., Erushin, E., Miroshnichenko, I., Kostyukova, N., Boyko, A. & Redyuk, A., Sept 2023, In: Infrared Physics and Technology. 133, 6 p., 104821.

    Research output: Contribution to journal › Article › peer-review

  15. Scheme of Signal Processing in a Multimode Communication Receiver Based on Convolutional Neural Networks

    Sidelnikov, O. S., Redyuk, A. A. & Fedoruk, M. P., Sept 2023, In: Bulletin of the Lebedev Physics Institute. 50, p. S336-S342 7 p.

    Research output: Contribution to journal › Article › peer-review

  16. 2022

  17. Схема обработки сигналов в приемнике многомодовых линий связи на основе сверточных нейронных сетей

    Сидельников, О. С., Редюк, А. А. & Федорук, М. П., 18 Oct 2022, p. 145-146. 2 p.

    Research output: Contribution to conference › Abstract › peer-review

  18. Применение методов машинного обучения для калибровки газового датчика

    Козьмин, А. Д. & Редюк, А. А., 2022, p. 54. 1 p.

    Research output: Contribution to conference › Abstract › peer-review

  19. Схема обработки сигналов в приемнике многомодовых линий связи на основе сверточных нейронных сетей

    Сидельников, О. С., Редюк, А. А. & Федорук, М. П., 2022, In: Квантовая электроника. 52, 11, p. 1018-1022 5 p., 10.

    Research output: Contribution to journal › Article › peer-review

  20. 2021

  21. Application of complex fully connected neural networks to compensate for nonlinearity in fibre-optic communication lines with polarisation division multiplexing

    Bogdanov, S. A., Sidelnikov, O. S. & Redyuk, A. A., Dec 2021, In: Quantum Electronics. 51, 12, p. 1076-1080 5 p., 5.

    Research output: Contribution to journal › Article › peer-review

  22. Interchannel nonlinearity compensation using a perturbative machine learning technique

    Kozulin, I. A. & Redyuk, A. A., 15 Aug 2021, In: Optics Communications. 493, 127026.

    Research output: Contribution to journal › Article › peer-review

  23. Convolutional Neural Networks with Multiple Layers per Span for Nonlinearity Mitigation in Long-Haul WDM Transmission Systems

    Sidelnikov, O., Redyuk, A., Sygletos, S., Fedoruk, M. & Turitsyn, S., Jun 2021, 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021. Institute of Electrical and Electronics Engineers Inc., 1 p. Paper CI-P.6. (2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  24. Advanced Convolutional Neural Networks for Nonlinearity Mitigation in Long-Haul WDM Transmission Systems

    Sidelnikov, O., Redyuk, A., Sygletos, S., Fedoruk, M. & Turitsyn, S. K., 15 Apr 2021, In: Journal of Lightwave Technology. 39, 8, p. 2397-2406 10 p., 9324921.

    Research output: Contribution to journal › Article › peer-review

  25. Convolutional neural networks with multiple layers per span for nonlinearity mitigation in long-haul WDM transmission systems

    Sidelnikov, O., Redyuk, A., Sygletos, S., Fedoruk, M. & Turitsyn, S., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, ci_p_6. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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