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  1. 2021

  2. 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

  3. 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

  4. 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

  5. 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

  6. 2022

  7. 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

  8. 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

  9. 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

  10. 2023

  11. 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

  12. 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

  13. 2024

  14. 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

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