Konev Viktor Vasil'evich

Publications in Math-Net.Ru

1. Confidence estimation of autoregressive parameters based on noisy data
   
   Avtomat. i Telemekh., 2021, no. 6,  124–148
2. On sequential confidence estimation of parameters of stochastic dynamical systems with conditionally Gaussian noises
   
   Avtomat. i Telemekh., 2017, no. 10,  90–108
3. On sequential estimation of the parameters of continuous-time trigonometric regression
   
   Avtomat. i Telemekh., 2016, no. 6,  61–80
4. On sequential estimation of a periodic signal on the background of an autoregressive noise
   
   Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2015, no. 2(34),  18–29
5. Estimation of the regression with a pulse noise by discrete time observations
   
   Teor. Veroyatnost. i Primenen., 58:3 (2013),  454–471
6. On the sequential estimation of parameters in a continuous autoregression model
   
   Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2013, no. 5(25),  12–25
7. Estimation of the parametric regression with a pulse noise by discrete time observations
   
   Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2012, no. 1(17),  20–35
8. Nonparametric estimation in a semimartingale regression model. Part 2. Robust asymptotic efficiency
   
   Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2009, no. 4(8),  31–45
9. Non-parametric estimation in a semimartingale regression model. Part 1. Oracle inequalities
   
   Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2009, no. 3(7),  23–41
10. Successive identification of the random-parameter linear dynamic system
    
    Avtomat. i Telemekh., 2008, no. 8,  82–95
11. On Guaranteed Estimation of the Spectral Density of an Autoregression?Moving Average Process
    
    Probl. Peredachi Inf., 38:1 (2002),  92–107
12. On the Guaranteed Parameter Estimation in Linear Regression Subject to Dependent Noise
    
    Avtomat. i Telemekh., 1997, no. 2,  75–87
13. Guaranteed Estimation of a Periodic Signal Distorted by an Autoregressive Noise with Unknown Parameters
    
    Probl. Peredachi Inf., 33:4 (1997),  26–44
14. The prescribed precision estimators of the autoregression parameter using the generalized least square method
    
    Teor. Veroyatnost. i Primenen., 41:4 (1996),  765–784
15. On the mean number of observations under guaranteed estimation of an autoregression parameter
    
    Avtomat. i Telemekh., 1995, no. 6,  97–104
16. On Sequential Classification of Autoregressive Processes with Unknown Variance of Noise
    
    Probl. Peredachi Inf., 31:4 (1995),  51–62
17. On the estimation of an autoregressive parameter on the basis of the generalized method of least squares
    
    Uspekhi Mat. Nauk, 50:6(306) (1995),  187–188
18. Guaranteed estimation of autoregression parameters under unknown noise variance
    
    Avtomat. i Telemekh., 1994, no. 2,  87–99
19. Guaranteed estimation of autoregression parameters on the basis of a sequential correlational method
    
    Trudy Mat. Inst. Steklov., 202 (1993),  149–169
20. Characteristics of a procedure for the detection of sudden change in an autoregression process with an unknown noise distribution
    
    Avtomat. i Telemekh., 1992, no. 2,  68–75
21. Sequential Parameter Estimation with Guaranteed Mean-Square Accuracy for Unstable Linear Stochastic Systems
    
    Probl. Peredachi Inf., 28:4 (1992),  35–48
22. Change-Point Detection in a Linear Stochastic System from Noisy Observations
    
    Probl. Peredachi Inf., 28:3 (1992),  68–75
23. On the detection of change points in dynamical systems
    
    Avtomat. i Telemekh., 1990, no. 3,  56–68
24. Optimality of Sequential Estimation Plans for the Parameters of Recursive Processes
    
    Probl. Peredachi Inf., 26:1 (1990),  108–111
25. On guaranteed parameter estimation for unstable dynamic systems
    
    Avtomat. i Telemekh., 1988, no. 11,  130–141
26. Sequential parameter estimation for dynamical systems in the presence of multiplicative and additive noises in the observations
    
    Avtomat. i Telemekh., 1985, no. 6,  33–43
27. On Sequential Estimation of Parameters of Diffusion Processes
    
    Probl. Peredachi Inf., 21:1 (1985),  48–61
28. Asymptotic normality of sequential parameter estimation for dynamic systems
    
    Avtomat. i Telemekh., 1984, no. 12,  56–63
29. A sequential method for detection of faults in random processes of the recurrent type
    
    Avtomat. i Telemekh., 1984, no. 5,  27–38
30. Bounds for the mean time of reaching a constant threshold by a non-anticipative functional of a random process of recurrent type
    
    Uspekhi Mat. Nauk, 39:1(235) (1984),  139–140
31. The boundaries for the mean number of observations in problems of sequential parameter estimation for recurrent processes
    
    Avtomat. i Telemekh., 1983, no. 8,  64–73
32. A sequential method of nonlinear parameter estimation for random processes
    
    Avtomat. i Telemekh., 1982, no. 12,  39–47
33. On the mean observation time in sequential estimation of recurrent process parameters
    
    Avtomat. i Telemekh., 1981, no. 10,  90–97
34. Successive procedures of parameter identification in dynamic systems
    
    Avtomat. i Telemekh., 1981, no. 7,  84–92
35. Sequential estimation of discrete-time process parameters
    
    Avtomat. i Telemekh., 1977, no. 10,  58–64
36. The error in the statistical estimation of multiple integrals using the $\omega ^{2}$-test
    
    Zh. Vychisl. Mat. Mat. Fiz., 17:6 (1977),  1363–1373


37. In memory of Prof. G. G. Pestov: life and scientific-educational activity
    
    Vestn. Tomsk. Gos. Univ. Mat. Mekh., 2015, no. 5(37),  103–114