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Borisov Andrey Vladimirovich

Publications in Math-Net.Ru

  1. Optimization of a train speed profile based on the expected accident damage criterion

    Inform. Primen., 19:3 (2025),  27–35
  2. Mathematical support for monitoring of states and numerical characteristics of network connection based on compound statistical information

    Inform. Primen., 19:2 (2025),  35–44
  3. Filtering of states and parameters of special Markov jump processes via indirect perfect observations

    Inform. Primen., 19:1 (2025),  25–32
  4. Filtering of a class of Markov jump processes by heterogeneous observations with additive noises

    Inform. Primen., 18:4 (2024),  10–18
  5. Probabilistic analysis of a class of Markov jump processes

    Inform. Primen., 18:3 (2024),  30–37
  6. Market with Markov jump volatility V: Market completion with derivatives

    Inform. Primen., 18:2 (2024),  9–16
  7. Market with markov jump volatility IV: price of risk monitoring algorithm given high frequency observation flows of assets prices

    Inform. Primen., 18:1 (2024),  26–32
  8. Market with Markov jump volatility III: Price of risk monitoring algorithm given discrete-time observations of asset prices

    Inform. Primen., 17:4 (2023),  9–16
  9. Market with Markov jump volatility II: Algorithm of derivative fair price calculation

    Inform. Primen., 17:3 (2023),  18–24
  10. Market with Markov jump volatility I: Price of risk monitoring as an optimal filtering problem

    Inform. Primen., 17:2 (2023),  27–33
  11. $\mathcal {L}_1$-optimal filtering of Markov jump processes. III. Identification of system parameters

    Avtomat. i Telemekh., 2022, no. 11,  121–144
  12. Practical implementation of the solution of the stabilization problem for a linear system with discontinuous random drift by indirect observations

    Avtomat. i Telemekh., 2022, no. 9,  109–127
  13. Total approximation order for Markov jump process filtering given discretized observations

    Inform. Primen., 16:4 (2022),  8–13
  14. Research and development strategy in the field of artificial intelligence IV: Chinese government policy

    Sistemy i Sredstva Inform., 32:1 (2022),  18–33
  15. Information aspects of security in transport: Analytical data processing

    Sistemy i Sredstva Inform., 32:1 (2022),  4–17
  16. Filtering of Markov jump processes given composite observations II: Numerical algorithm

    Inform. Primen., 15:3 (2021),  9–15
  17. Filtering of Markov jump processes given composite observations I: Exact solution

    Inform. Primen., 15:2 (2021),  12–19
  18. Research and development strategy in the field of artificial intellegence III: United States government support doctrine

    Sistemy i Sredstva Inform., 31:4 (2021),  114–134
  19. Information aspects of security in transport: Analytical calculations

    Sistemy i Sredstva Inform., 31:4 (2021),  97–113
  20. Research and development strategy in the field of artificial intellegence II: Comparative analysis of scientometric indicators in the world and in the Russian Federation

    Sistemy i Sredstva Inform., 31:2 (2021),  89–107
  21. Information aspects of security in transport: Search and selection of information

    Sistemy i Sredstva Inform., 31:2 (2021),  80–88
  22. Research and development strategy in the field of artificial intelligence I: Basic concepts and brief chronology

    Sistemy i Sredstva Inform., 31:1 (2021),  57–68
  23. $\mathcal{L}_1$-optimal filtering of Markov jump processes. II. Numerical analysis of particular realizations schemes

    Avtomat. i Telemekh., 2020, no. 12,  24–49
  24. $\mathcal{L}_1$-optimal filtering of Markov jump processes. I. Exact solution and numerical implementation schemes

    Avtomat. i Telemekh., 2020, no. 11,  11–31
  25. Robust filtering algorithm for Markov jump processes with high-frequency counting observations

    Avtomat. i Telemekh., 2020, no. 4,  3–20
  26. Numerical schemes of Markov jump process filtering given discretized observations III: Multiplicative noises case

    Inform. Primen., 14:2 (2020),  10–18
  27. Numerical schemes of Markov jump process filtering given discretized observations II: Additive noise case

    Inform. Primen., 14:1 (2020),  17–23
  28. Information aspects of security in transport: Ontology of the subject area, models, and cases

    Sistemy i Sredstva Inform., 30:1 (2020),  126–134
  29. Numerical schemes of Markov jump process filtering given discretized observations I: Accuracy characteristics

    Inform. Primen., 13:4 (2019),  68–75
  30. Wonham filtering by observations with multiplicative noises

    Avtomat. i Telemekh., 2018, no. 1,  52–65
  31. The conditionally minimax nonlinear filtering method and modern approaches to state estimation in nonlinear stochastic systems

    Avtomat. i Telemekh., 2018, no. 1,  3–17
  32. Filtering of Markov jump processes by discretized observations

    Inform. Primen., 12:3 (2018),  115–121
  33. Analytical information systems performance analysis: methodology for timetable and staff quantity evaluation

    Sistemy i Sredstva Inform., 28:3 (2018),  39–53
  34. Monte Carlo based user activity simulation for software performance evaluation

    Sistemy i Sredstva Inform., 28:2 (2018),  20–33
  35. To the reliability of an information-telecommunication system: an approach to recognition of reliable software characteristics

    Sistemy i Sredstva Inform., 28:1 (2018),  20–34
  36. Classification by continuous-time observations in multiplicative noise II: numerical algorithm

    Inform. Primen., 11:2 (2017),  33–41
  37. Classification by continuous-time observations in multiplicative noise I: formulae for Bayesian estimate

    Inform. Primen., 11:1 (2017),  11–19
  38. Application of optimal filtering methods for on-line of queueing network states

    Avtomat. i Telemekh., 2016, no. 2,  115–141
  39. Modeling and monitoring of VoIP connection

    Inform. Primen., 10:2 (2016),  2–13
  40. Filtering of the Markov jump process given the observations of multivariate point process

    Avtomat. i Telemekh., 2015, no. 2,  34–60
  41. Monitoring remote server accessibility: the optimal filtering approach

    Inform. Primen., 8:3 (2014),  53–69
  42. A posteriori minimax estimation with likelihood constraints

    Avtomat. i Telemekh., 2012, no. 9,  49–71
  43. Minimax estimation in systems of observation with Markovian chains by integral criterion

    Avtomat. i Telemekh., 2011, no. 2,  41–55
  44. Optimal estimates for the operating parameters of an information web portal

    Avtomat. i Telemekh., 2010, no. 3,  16–33
  45. Minimax a posteriori estimation of the Markov processes with finite state spaces

    Avtomat. i Telemekh., 2008, no. 2,  64–79
  46. Minimax a posteriori estimation in the hidden Markov models

    Avtomat. i Telemekh., 2007, no. 11,  31–45
  47. Specific optimal estimation of special Markov jump processes

    Avtomat. i Telemekh., 2007, no. 3,  47–65
  48. Bayesian estimation in observation systems with Markov jump processes: game-theoretic approach

    Inform. Primen., 1:2 (2007),  65–75
  49. Backward representation of Markov jump processes and related problems. II. Optimal nonlinear estimation

    Avtomat. i Telemekh., 2006, no. 9,  120–141
  50. Backward representation of Markov jump processes and related problems. I. Optimal linear estimation

    Avtomat. i Telemekh., 2006, no. 8,  51–76
  51. Algorithms of optimal non-linear smoothing of special Markovian jump processes

    Sistemy i Sredstva Inform., 2006, no. special issue,  47–76
  52. Analysis of hidden Markov models states generated by special jump processes

    Teor. Veroyatnost. i Primenen., 51:3 (2006),  589–600
  53. Analysis and filtration of special discrete-time markov processes. II. Optimal filtration

    Avtomat. i Telemekh., 2005, no. 7,  112–125
  54. Analysis and filtration of special discrete-time Markov processes. I. Martingale representation

    Avtomat. i Telemekh., 2005, no. 6,  114–125
  55. Analysis and estimation of the states of special jump Markov processes. II. Optimal filtration in wiener noise

    Avtomat. i Telemekh., 2004, no. 5,  61–76
  56. Analysis and estimation of the states of special Markov jump processes. I. A martingale representation

    Avtomat. i Telemekh., 2004, no. 1,  50–65
  57. Optimal filtering in systems with degenerate noise in observations

    Avtomat. i Telemekh., 1998, no. 11,  32–45
  58. Minimax linear estimation in generalized uncertain-stochastic system. II. Minimax filtering in dynamic systems described by stochastic differential equations with measure

    Avtomat. i Telemekh., 1998, no. 6,  139–152
  59. Minimax linear estimation in generalized uncertain-stochastic systems. I: Estimation of random elements with values in Hilbert spaces

    Avtomat. i Telemekh., 1998, no. 5,  102–111
  60. Minimax Estimation of Stochastic Elements with Values in Hilbert Spaces

    Avtomat. i Telemekh., 1996, no. 6,  61–75
  61. Minimax procedures for statistical estimation in Hilbert spaces

    Dokl. Akad. Nauk, 345:6 (1995),  727–729
  62. Minimax estimation in linear differential indeterminate-stochastic systems

    Avtomat. i Telemekh., 1992, no. 4,  57–63
  63. Filtering and smoothing in nondeterministic-stochastic systems with partially observable inputs

    Avtomat. i Telemekh., 1991, no. 3,  85–95


© Steklov Math. Inst. of RAS, 2026