11 citations to https://www.mathnet.ru/rus/tvp4611
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Yash Deshmukh, Ankit Kumar Mishra, Shreya Mane, Rishab Gupta, Vasudha Kunjir, INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN SCIENCE AND TECHNOLOGY (RIST2022), 3037, INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN SCIENCE AND TECHNOLOGY (RIST2022), 2024, 020024
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E. V. Burnaev, “On construction of early warning systems for predictive maintenance in aerospace industry”, J. Commun. Technol. Electron., 64:12 (2019), 1473–1484
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R. Rivera-Castro, I. Nazarov, Yu. Xiang, A. Pletneev, I. Maksimov, E. Burnaev, “Demand forecasting techniques for build-to-order lean manufacturing supply chains”, Advances in Neural Networks - Isnn 2019, Pt i, Lecture Notes in Computer Science, 11554, eds. H. Lu, H. Tang, Z. Wang, Springer, 2019, 213–222
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D. Smolyakov, N. Sviridenko, V. Ishimtsev, E. Burikov, E. Burnaev, “Learning ensembles of anomaly detectors on synthetic data”, Advances in Neural Networks - Isnn 2019, Pt II, Lecture Notes in Computer Science, 11555, eds. H. Lu, H. Tang, Z. Wang, Springer, 2019, 292–306
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Evgeny Burnaev, 2019 3rd International Conference on Circuits, System and Simulation (ICCSS), 2019, 214
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P. Chigansky, M. Kleptsyna, “Statistical analysis of the mixed fractional Ornstein–Uhlenbeck process”, Теория вероятн. и ее примен., 63:3 (2018), 500–519 ; Theory Probab. Appl., 63:3 (2019), 408–425
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B. L. S. Prakasa Rao, “Berry-Esseen type bound for fractional Ornstein-Uhlenbeck type process driven by sub-fractional Brownian motion”, Theory Stoch. Process., 23(39):1 (2018), 82–92
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B. L. S. Prakasa Rao, “Optimal estimation of a signal perturbed by a sub-fractional Brownian motion”, Stoch. Anal. Appl., 35:3 (2017), 533–541
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B.L.S. Prakasa Rao, “Optimal estimation of a signal perturbed by a mixed fractional Brownian motion”, Theory Stoch. Process., 22(38):2 (2017), 62–68
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Artemov A., Burnaev E., “Detecting Performance Degradation of Software-Intensive Systems in the Presence of Trends and Long-Range Dependence”, 2016 IEEE 16Th International Conference on Data Mining Workshops (Icdmw), International Conference on Data Mining Workshops, eds. Domeniconi C., Gullo F., Bonchi F., DomingoFerrer J., BaezaYates R., Zhou ZH., Wu X., IEEE, 2016, 29–36