Borisov Andrey Vladimirovich

Publications in Math-Net.Ru

1. Filtering of states and parameters of special Markov jump processes via indirect perfect observations
   
   Inform. Primen., 19:1 (2025),  25–32
2. Filtering of a class of Markov jump processes by heterogeneous observations with additive noises
   
   Inform. Primen., 18:4 (2024),  10–18
3. Probabilistic analysis of a class of Markov jump processes
   
   Inform. Primen., 18:3 (2024),  30–37
4. Market with Markov jump volatility V: Market completion with derivatives
   
   Inform. Primen., 18:2 (2024),  9–16
5. 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
6. 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
7. Market with Markov jump volatility II: Algorithm of derivative fair price calculation
   
   Inform. Primen., 17:3 (2023),  18–24
8. Market with Markov jump volatility I: Price of risk monitoring as an optimal filtering problem
   
   Inform. Primen., 17:2 (2023),  27–33
9. $\mathcal {L}_1$-optimal filtering of Markov jump processes. III. Identification of system parameters
   
   Avtomat. i Telemekh., 2022, no. 11,  121–144
10. 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
11. Total approximation order for Markov jump process filtering given discretized observations
    
    Inform. Primen., 16:4 (2022),  8–13
12. Research and development strategy in the field of artificial intelligence IV: Chinese government policy
    
    Sistemy i Sredstva Inform., 32:1 (2022),  18–33
13. Information aspects of security in transport: Analytical data processing
    
    Sistemy i Sredstva Inform., 32:1 (2022),  4–17
14. Filtering of Markov jump processes given composite observations II: Numerical algorithm
    
    Inform. Primen., 15:3 (2021),  9–15
15. Filtering of Markov jump processes given composite observations I: Exact solution
    
    Inform. Primen., 15:2 (2021),  12–19
16. 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
17. Information aspects of security in transport: Analytical calculations
    
    Sistemy i Sredstva Inform., 31:4 (2021),  97–113
18. 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
19. Information aspects of security in transport: Search and selection of information
    
    Sistemy i Sredstva Inform., 31:2 (2021),  80–88
20. 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
21. $\mathcal{L}_1$-optimal filtering of Markov jump processes. II. Numerical analysis of particular realizations schemes
    
    Avtomat. i Telemekh., 2020, no. 12,  24–49
22. $\mathcal{L}_1$-optimal filtering of Markov jump processes. I. Exact solution and numerical implementation schemes
    
    Avtomat. i Telemekh., 2020, no. 11,  11–31
23. Robust filtering algorithm for Markov jump processes with high-frequency counting observations
    
    Avtomat. i Telemekh., 2020, no. 4,  3–20
24. Numerical schemes of Markov jump process filtering given discretized observations III: Multiplicative noises case
    
    Inform. Primen., 14:2 (2020),  10–18
25. Numerical schemes of Markov jump process filtering given discretized observations II: Additive noise case
    
    Inform. Primen., 14:1 (2020),  17–23
26. Information aspects of security in transport: Ontology of the subject area, models, and cases
    
    Sistemy i Sredstva Inform., 30:1 (2020),  126–134
27. Numerical schemes of Markov jump process filtering given discretized observations I: Accuracy characteristics
    
    Inform. Primen., 13:4 (2019),  68–75
28. Wonham filtering by observations with multiplicative noises
    
    Avtomat. i Telemekh., 2018, no. 1,  52–65
29. The conditionally minimax nonlinear filtering method and modern approaches to state estimation in nonlinear stochastic systems
    
    Avtomat. i Telemekh., 2018, no. 1,  3–17
30. Filtering of Markov jump processes by discretized observations
    
    Inform. Primen., 12:3 (2018),  115–121
31. Analytical information systems performance analysis: methodology for timetable and staff quantity evaluation
    
    Sistemy i Sredstva Inform., 28:3 (2018),  39–53
32. Monte Carlo based user activity simulation for software performance evaluation
    
    Sistemy i Sredstva Inform., 28:2 (2018),  20–33
33. 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
34. Classification by continuous-time observations in multiplicative noise II: numerical algorithm
    
    Inform. Primen., 11:2 (2017),  33–41
35. Classification by continuous-time observations in multiplicative noise I: formulae for Bayesian estimate
    
    Inform. Primen., 11:1 (2017),  11–19
36. Application of optimal filtering methods for on-line of queueing network states
    
    Avtomat. i Telemekh., 2016, no. 2,  115–141
37. Modeling and monitoring of VoIP connection
    
    Inform. Primen., 10:2 (2016),  2–13
38. Filtering of the Markov jump process given the observations of multivariate point process
    
    Avtomat. i Telemekh., 2015, no. 2,  34–60
39. Monitoring remote server accessibility: the optimal filtering approach
    
    Inform. Primen., 8:3 (2014),  53–69
40. A posteriori minimax estimation with likelihood constraints
    
    Avtomat. i Telemekh., 2012, no. 9,  49–71
41. Minimax estimation in systems of observation with Markovian chains by integral criterion
    
    Avtomat. i Telemekh., 2011, no. 2,  41–55
42. Optimal estimates for the operating parameters of an information web portal
    
    Avtomat. i Telemekh., 2010, no. 3,  16–33
43. Minimax a posteriori estimation of the Markov processes with finite state spaces
    
    Avtomat. i Telemekh., 2008, no. 2,  64–79
44. Minimax a posteriori estimation in the hidden Markov models
    
    Avtomat. i Telemekh., 2007, no. 11,  31–45
45. Specific optimal estimation of special Markov jump processes
    
    Avtomat. i Telemekh., 2007, no. 3,  47–65
46. Bayesian estimation in observation systems with Markov jump processes: game-theoretic approach
    
    Inform. Primen., 1:2 (2007),  65–75
47. Backward representation of Markov jump processes and related problems. II. Optimal nonlinear estimation
    
    Avtomat. i Telemekh., 2006, no. 9,  120–141
48. Backward representation of Markov jump processes and related problems. I. Optimal linear estimation
    
    Avtomat. i Telemekh., 2006, no. 8,  51–76
49. Algorithms of optimal non-linear smoothing of special Markovian jump processes
    
    Sistemy i Sredstva Inform., 2006, no. special issue,  47–76
50. Analysis of hidden Markov models states generated by special jump processes
    
    Teor. Veroyatnost. i Primenen., 51:3 (2006),  589–600
51. Analysis and filtration of special discrete-time markov processes. II. Optimal filtration
    
    Avtomat. i Telemekh., 2005, no. 7,  112–125
52. Analysis and filtration of special discrete-time Markov processes. I. Martingale representation
    
    Avtomat. i Telemekh., 2005, no. 6,  114–125
53. 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
54. Analysis and estimation of the states of special Markov jump processes. I. A martingale representation
    
    Avtomat. i Telemekh., 2004, no. 1,  50–65
55. Optimal filtering in systems with degenerate noise in observations
    
    Avtomat. i Telemekh., 1998, no. 11,  32–45
56. 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
57. 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
58. Minimax Estimation of Stochastic Elements with Values in Hilbert Spaces
    
    Avtomat. i Telemekh., 1996, no. 6,  61–75
59. Minimax procedures for statistical estimation in Hilbert spaces
    
    Dokl. Akad. Nauk, 345:6 (1995),  727–729
60. Minimax estimation in linear differential indeterminate-stochastic systems
    
    Avtomat. i Telemekh., 1992, no. 4,  57–63
61. Filtering and smoothing in nondeterministic-stochastic systems with partially observable inputs
    
    Avtomat. i Telemekh., 1991, no. 3,  85–95