1. 2024
  2. 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 journalArticlepeer-review

  3. 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 journalArticlepeer-review

  4. 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 journalArticlepeer-review

  5. 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 journalArticlepeer-review

  6. 2023
  7. 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 journalArticlepeer-review

  8. 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 journalArticlepeer-review

  9. 2022

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