Статьи

• Mehmet Tahir Huyut, Andrei Velichko LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19, MethodsX, Volume 10, 2023, 102194, ISSN 2215-0161, https://doi.org/10.1016/j.mex.2023.102194. (Web of Science, Scopus)
• Heidari, H., Velichko, A., Murugappan, M. et al. Novel techniques for improving NNetEn entropy calculation for short and noisy time series. Nonlinear Dyn (2023). https://doi.org/10.1007/s11071-023-08298-w (Scopus, Web of Science)
• Huyut, M.T.; Velichko, A. Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network. Sensors 2022, 22, 4820. https://doi.org/10.3390/s22134820 (Web of Science, Scopus)
• Величко А.А. Entropy approximation by machine learning regression: application for irregularity evaluation of images in remote sensing [Text] / А.А. Величко, М.А. Беляев, M.. Wagner, A.. Taravat // Remote sensing. - Швейцария, 2022. - vol.14, №.23. - P.1-25. - URL: https://doi.org/10.3390/rs14235983. - ISSN 2072-4292. (Scopus)
• Velichko A.A. Machine learning sensors for diagnosis of covid-19 disease using routine blood values for internet of things application [Text] / A.A. Velichko, M.T. Huyut, M.A. Belyaev, Yu.A. Izotov, D.Zh. Korzun // Sensors. - Швейцария, 2022. - vol.22. - P.1-30. - URL: https://www.mdpi.com/1424-8220/22/20/7886. - ISSN 1424-8220. (Scopus, Web of Science)
• Oludehinwa, IA Dynamical Complexity Response in Traveling Ionospheric Disturbances Across Eastern Africa Sector During Geomagnetic Storms Using Neural Network Entropy [Electronic resource] / Oludehinwa, IA; Velichko, A; Ogunsua, BO; Olusola, OI; Odeyemi, OO; Njah, AN; Ologun, OT // JGR: Space Physics. - USA, 2022. - vol.127, N9. - P.1-27. - ISSN 2169-9402. (Scopus, Web of Science)
• Velichko, A.; Wagner, M.P.; Taravat, A.; Hobbs, B.; Ord, A. NNetEn2D: Two-Dimensional Neural Network Entropy in Remote Sensing Imagery and Geophysical Mapping. Remote Sens. 2022, 14, 2166. https://doi.org/10.3390/rs14092166 (Scopus, Web of Science)
• Huyut M.T. Detection of risk predictors of covid-19 mortality with classifier machine learning models operated with routine laboratory biomarkers [Text] / M.T. Huyut, А.А. Величко, М.А. Беляев // Applied sciences. - Швейцария, 2022. - vol.12, №.23. - P.1-26. - URL: https://www.mdpi.com/2076-3417/12/23/12180. - ISSN 2076-3417. (Scopus, Web of Science)
• Boriskov P.P. Bifurcation and entropy analysis of a chaotic spike oscillator circuit based on the s-switch [Text] / P.P. Boriskov, A.A. Velichko, N.A. Shilovskiy, M.A. Belyaev // Entropy. - Швейцария, 2022. - vol.24, №.1693. - P.1-15. (Web of Science, Scopus)
• Velichko, A.; Heidari, H. A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks. Entropy 2021, 23, 1432. https://doi.org/10.3390/e23111432 (Scopus, Web of Science)
• Величко, А.А. A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare [Electronic resource] / А.А. Величко // Sensors. - Switzerland, 2021. - vol.18. - P.1-21. - URL: https://www.mdpi.com/1424-8220/21/18/6209. (Scopus, Web of Science)
• Величко А.А. Concept of LIF Neuron Circuit for Rate Coding in Spike Neural Networks [Text] / А.А. Величко, П.П. Борисков // IEEE Transactions on Circuits and Systems II: Express Briefs. - USA, 2020. - vol.67, N12. - P.3477-3481. - URL: https://ieeexplore.ieee.org/document/9099234?source=authoralert. - ISSN 1558-3791. (Scopus, Web of Science)
• Velichko, A. Neural Network for Low-Memory IoT Devices and MNIST Image Recognition Using Kernels Based on Logistic Map. Electronics 2020, 9, 1432, doi:10.3390/electronics9091432. (Web of Science, Scopus)
• Величко А.А. Higher-order and long-range synchronization effects for classification and computing in oscillator-based spiking neural networks [Text] / А.А. Величко, В.В. Путролайнен, М.А. Беляев // Neural Computing and Applications. - London, UK, 2020. - P.1-19. - ISSN 0941-0643. (Web of Science, Scopus)
• Беляев М.А. Examination of the Dynamic Threshold Characteristics of a VO2 Switch in an Oscillatory Circuit [Text] / М.А. Беляев, А.А. Величко // Technical Physics Letters. - Берлин, 2020. - vol.46, N2. - P.137-140. (ВАК, Web of Science, Scopus)
• Беляев М.А. A Spiking Neural Network Based on the Model of VO2–Neuron [Текст] / М.А. Беляев, А.А. Величко // Electronics. - Швейцария, 2019. - Т.8, вып.10. - С.1065. (Web of Science, Scopus, ВАК)
• Борисков П.П. Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators [Electronic resource] / П.П. Борисков, А.А. Величко // Electronics. - Швейцария, 2019. - vol.8, N9. - P.922. - ISSN 2079-9292. (Web of Science, Scopus)
• Velichko, A. A Method for Evaluating Chimeric Synchronization of Coupled Oscillators and Its Application for Creating a Neural Network Information Converter. Electronics 2019, 8, 756, doi:10.3390/electronics8070756. (Web of Science, Scopus)
• Velichko, A.; Belyaev, M.; Boriskov, P. A Model of an Oscillatory Neural Network with Multilevel Neurons for Pattern Recognition and Computing. Electronics 2019, 8, 75, doi:10.3390/electronics8010075. (Web of Science, Scopus)
• An Investigation of the Effect of the Thermal Coupling Time Delay on the Synchronization of VO2-Oscillators [Текст] / М.А. Беляев, А.А. Величко // Technical Physics Letters. - Switzerland, 2019. - Т.45, вып.2. - С.61-64. - ISSN 1063-7850. (ВАК, Web of Science, Scopus)