1. 2023
  2. Application of Machine Learning to Diagnostics of Schizophrenia Patients Based on Event-Related Potentials

    Шанарова, Н. Л., Пронина, М. В., Липкович, М., Пономарев, В., Muller, A. & Кропотов, Ю. Д., 30 Jan 2023, In: Diagnostics. 13, 3

    Research output: Contribution to journalArticlepeer-review

  3. 2022
  4. Modeling pulsativity in the hypothalamic–pituitary–adrenal hormonal axis

    Churilov, A. N. & Milton, J. G., Dec 2022, In: Scientific Reports. 12, 1, p. 8480 8480.

    Research output: Contribution to journalArticlepeer-review

  5. Controlled synchronization in regular delay-coupled networks of Hindmarsh-Rose neurons

    Semenov, D. M., Plotnikov, S. A. & Fradkov, A. L., 21 Oct 2022, Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022. Institute of Electrical and Electronics Engineers Inc., p. 236-239 4 p. (Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

  6. Machine learning based diagnostics of schizophrenia patients

    Shanarova, N., Pronina, M., Lipkovich, M. & Kropotov, J., 21 Oct 2022, Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022. Institute of Electrical and Electronics Engineers Inc., p. 252-255 4 p. (Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

  7. Speed-Gradient approach to Hindmarsh-Rose model identification based on membrane potential measurements

    Kovalchukov, A. & Fradkov, A. L., 21 Oct 2022, Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022. Institute of Electrical and Electronics Engineers Inc., p. 151-154 4 p. (Proceedings - 6th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2022).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

  8. Identification of the FitzHugh-Nagumo Neuron Model Based on the Speed-Gradient and Filtering

    Fradkov, A., Shepeljavyi, A. & Rybalko, A., 17 Oct 2022, Proceedings - 4th International Conference "Neurotechnologies and Neurointerfaces", CNN 2022. Institute of Electrical and Electronics Engineers Inc., p. 29-31 3 p. (Proceedings - 4th International Conference "Neurotechnologies and Neurointerfaces", CNN 2022).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

  9. Классификация сигналов электроэнцефалограмм человека на определение намерения совершить движение

    Шанарова, Н. Л., Липкович, М., Волошина, А. И., Александров, А. А. & Князева, В. М., 5 Oct 2022, (E-pub ahead of print) 15-я Мультиконференция по проблемам управления (МКПУ-2022), 4-6 октября 2022 г., г. СПб. p. 148-150

    Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

  10. Digital Adaptive Control of Unbalanced Rotor Velocities with Anti-windup Augmentation

    Andrievsky, B., Zaitceva, I., Boikov, V. I. & Fradkov, A. L., Aug 2022, (E-pub ahead of print) In: IFAC-PapersOnLine. 55, 12, p. 258-263

    Research output: Contribution to journalArticlepeer-review

  11. Extreme value theory inspires explainable machine learning approach for seizure detection

    Karpov, O. E., Grubov, V. V., Maksimenko, V. A., Kurkin, S. A., Smirnov, N. M., Utyashev, N. P., Andrikov, D. A., Shusharina, N. N. & Hramov, A. E., 6 Jul 2022, In: Scientific Reports. 12, 1, 14 p., 11474.

    Research output: Contribution to journalArticlepeer-review

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