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Shestakov, Oleg Vladimirovich
Statistics Math-Net.Ru
Total publications: 55
Scientific articles: 55
Presentations: 1

Number of views:
This page:1418
Abstract pages:10461
Full texts:3980
References:1896
Professor of Russian Academy of Sciences
Associate professor
Doctor of physico-mathematical sciences
Birth date: 4.12.1976
E-mail:

https://www.mathnet.ru/eng/person64354
https://ru.wikipedia.org/wiki/Shestakov,_Oleg_Vladimirovich
List of publications on Google Scholar
List of publications on ZentralBlatt
https://elibrary.ru/author_items.asp?authorid=17596
ISTINA https://istina.msu.ru/workers/438418
https://orcid.org/0000-0002-1157-1226
https://www.webofscience.com/wos/author/record/B-3496-2013
https://www.scopus.com/authid/detail.url?authorId=6603804676

Publications in Math-Net.Ru Citations
2024
1. M. O. Vorontsov, O. V. Shestakov, “Asymptotic normality and strong consistency of risk estimate when using the FDR threshold under weak dependence condition”, Inform. Primen., 18:3 (2024),  69–79  mathnet
2. A. A. Kudryavtsev, O. V. Shestakov, “Uniform convergence rate estimates for the integral balance index”, Inform. Primen., 18:1 (2024),  33–39  mathnet
2023
3. O. V. Shestakov, E. P. Stepanov, “Nonlinear regularization of the inversion of linear homogeneous operators using the block thresholding method”, Inform. Primen., 17:4 (2023),  2–8  mathnet
4. A. A. Kudryavtsev, O. V. Shestakov, “A method for estimating parameters of the gamma-exponential distribution from a sample with weakly dependent components”, Inform. Primen., 17:3 (2023),  58–63  mathnet 1
5. M. O. Vorontsov, O. V. Shestakov, “Mean-square risk of the FDR procedure under weak dependence”, Inform. Primen., 17:2 (2023),  34–40  mathnet 2
2022
6. O. V. Shestakov, “Unbiased thresholding risk estimate with two threshold values”, Inform. Primen., 16:4 (2022),  14–19  mathnet 2
7. S. I. Palionnaya, O. V. Shestakov, “The use of the FDR method of multiple hypothesis testing when inverting linear homogeneous operators”, Inform. Primen., 16:2 (2022),  44–51  mathnet
2021
8. A. A. Kudriavtsev, O. V. Shestakov, “Minimax estimates of the loss function based on integral error probabilities during threshold processing of wavelet coefficients”, Inform. Primen., 15:4 (2021),  12–19  mathnet 1
9. A. A. Kudryavtsev, O. V. Shestakov, S. Ya. Shorgin, “A method for estimating bent, shape and scale parameters of the gamma-exponential distribution”, Inform. Primen., 15:3 (2021),  57–62  mathnet 2
10. O. V. Shestakov, “Thresholding functions in the noise suppression methods based on the wavelet expansion of the signal”, Inform. Primen., 15:3 (2021),  51–56  mathnet 2
11. O. V. Shestakov, “Analysis of the unbiased mean-square risk estimate of the block thresholding method”, Inform. Primen., 15:2 (2021),  30–35  mathnet 3
12. M. O. Vorontsov, A. A. Kudryavtsev, O. V. Shestakov, “Some probability-statistical properties of the gamma-exponential distribution”, Sistemy i Sredstva Inform., 31:3 (2021),  18–35  mathnet 2
2020
13. A. A. Kudryavtsev, O. V. Shestakov, “Method of logarithmic moments for estimating the gamma-exponential distribution parameters”, Inform. Primen., 14:3 (2020),  49–54  mathnet 6
14. O. V. Shestakov, “On the statistical properties of risk estimate in the problem of inverting the Radon transform with a random volume of projection data”, Inform. Primen., 14:3 (2020),  44–48  mathnet
15. O. V. Shestakov, “Asymptotics of the mean-square risk estimate in the problem of inverting the Radon transform from projections registered on a random grid”, Inform. Primen., 14:2 (2020),  26–32  mathnet
16. O. V. Shestakov, “Asymptotic regularity of the wavelet methods of inverting linear homogeneous operators from observations recorded at random times”, Inform. Primen., 14:1 (2020),  3–9  mathnet
17. A. A. Kudryavtsev, O. V. Shestakov, “Average probability of error in calculating wavelet–vaguelette coefficients while inverting the Radon transform”, Sistemy i Sredstva Inform., 30:4 (2020),  14–24  mathnet
18. A. A. Kudriavtsev, O. V. Shestakov, “Estimation of the average error probability when calculating wavelet coefficients in the models with a long-term dependence”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2020, no. 1,  20–28  mathnet  elib
2019
19. O. V. Shestakov, “The mean square risk of nonlinear regularization in the problem of inversion of linear homogeneous operators with a random sample size”, Inform. Primen., 13:4 (2019),  48–53  mathnet
20. O. V. Shestakov, “Properties of wavelet estimates of signals recorded at random time points”, Inform. Primen., 13:2 (2019),  16–21  mathnet  elib 3
21. O. V. Shestakov, “Inversion of homogeneous operators using stabilized hard thresholding with unknown noise variance”, Inform. Primen., 13:1 (2019),  49–54  mathnet  elib
22. A. A. Kudryavtsev, S. I. Palionnaia, O. V. Shestakov, “Advantage index in Bayesian reliability and balance models with beta-polynomial a priori densities”, Sistemy i Sredstva Inform., 29:3 (2019),  29–38  mathnet
23. O. V. Shestakov, “Convergence of the distribution of the threshold processing risk estimate to a mixture of normal laws at a random sample size”, Sistemy i Sredstva Inform., 29:2 (2019),  31–38  mathnet 1
24. P. S. Popenova, O. V. Shestakov, “Analysis of statistical properties of the hybrid thresholding technique”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2019, no. 1,  15–22  mathnet  elib
2018
25. O. V. Shestakov, “Mean-square thresholding risk with a random sample size”, Inform. Primen., 12:3 (2018),  14–17  mathnet  elib 2
26. A. A. Kudryavtsev, O. V. Shestakov, “Minimization of errors of calculating wavelet coefficients while solving inverse problems”, Inform. Primen., 12:2 (2018),  17–23  mathnet  elib 1
27. O. V. Shestakov, “Unbiased risk estimate of stabilized hard thresholding in the model with a long-range dependence”, Inform. Primen., 12:2 (2018),  11–16  mathnet  elib
28. A. A. Kudryavtsev, O. V. Shestakov, “Bayesian models for testing large groups of service device”, Inform. Primen., 12:1 (2018),  105–108  mathnet  elib
29. A. I. Borisov, O. V. Shestakov, “Accuracy of reconstruction of the multidimensional probability density by wavelet estimates of one-dimensional projections”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2018, no. 1,  21–30  mathnet  elib
2017
30. O. V. Shestakov, “Universal thresholding in the models with non-Gaussian noise”, Inform. Primen., 11:2 (2017),  122–125  mathnet  elib
31. O. V. Shestakov, “Strong consistency of the mean square risk estimate in the inverse statistical problems”, Inform. Primen., 11:2 (2017),  117–121  mathnet  elib
32. A. A. Kudryavtsev, O. V. Shestakov, I. A. Fedushin, “Local reconstruction of tomographic images in parallel and fan-beam scanning schemes”, Sistemy i Sredstva Inform., 27:3 (2017),  52–62  mathnet  elib
33. A. Yu. Zaspa, O. V. Shestakov, “Consistency of the risk estimate of the multiple hypothesis testing with the FDR threshold”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2017, no. 1,  5–16  mathnet  elib 3
2016
34. T. V. Zakharova, O. V. Shestakov, “Precision analysis of wavelet processing of aerodynamic flow patterns”, Inform. Primen., 10:3 (2016),  46–54  mathnet  elib
35. O. V. Shestakov, “The strong law of large numbers for the risk estimate in the problem of tomographic image reconstruction from projections with a correlated noise”, Inform. Primen., 10:3 (2016),  41–45  mathnet  elib 1
36. O. V. Shestakov, “Statistical properties of the denoising method based on the stabilized hard thresholding”, Inform. Primen., 10:2 (2016),  65–69  mathnet  elib 3
37. A. A. Kudriavtsev, O. V. Shestakov, “Estimation of the optimal rate of the wavelet thresholding risk based on the error probabilities”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2016, no. 1,  5–12  mathnet  elib
2015
38. O. V. Shestakov, “Nonparametric estimation of multidimensional density with the use of wavelet estimates of univariate projections”, Inform. Primen., 9:2 (2015),  88–92  mathnet  elib 1
2014
39. A. A. Eroshenko, O. V. Shestakov, “Asymptotic properties of risk estimate in the problem of reconstructing images with correlated noise by inverting the Radon transform”, Inform. Primen., 8:4 (2014),  32–40  mathnet  elib 3
40. A. A. Eroshenko, O. V. Shestakov, “Asymptotic properties of wavelet thresholding risk estimate in the model of data with correlated noise”, Inform. Primen., 8:1 (2014),  36–44  mathnet  elib 3
41. M. Sh. Khaziakhmetov, T. V. Zakharova, O. V. Shestakov, “Properties of window dispersion increments of a myogram as a stochastic process”, Sistemy i Sredstva Inform., 24:4 (2014),  86–99  mathnet  elib
2013
42. O. V. Shestakov, M. G. Kuznetsova, I. A. Sadovoy, “Inversion of spherical Radon transform in the class of discrete random functions”, Inform. Primen., 7:4 (2013),  75–81  mathnet  elib
43. O. V. Shestakov, “On the rate of convergence to the normal law of risk estimate for wavelet coefficients thresholding when using robust variance estimates”, Inform. Primen., 7:2 (2013),  40–49  mathnet 3
2012
44. O. V. Shestakov, “On the rate of convergence to the normal law of risk estimate for wavelet coefficients thresholding when using robust variance estimates”, Inform. Primen., 6:2 (2012),  122–128  mathnet 4
45. O. V. Shestakov, “On the accuracy of normal approximation for risk estimate distribution when thresholding signal wavelet coefficients in case of unknown noise level”, Sistemy i Sredstva Inform., 22:1 (2012),  142–152  mathnet 3
46. O. V. Shestakov, “About properties of estimation of average-square risk when regularizing the inverse of a linear homogeneous operator with adaptive thresholding treatment of the vaguelette-wavelet definition coefficients”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2012, no. 1,  117–130  mathnet  elib
2011
47. O. V. Shestakov, “On the rate of convergence of sample median absolute deviation distribution to the normal law”, Inform. Primen., 5:3 (2011),  74–79  mathnet 1
48. V. G. Ushakov, O. V. Shestakov, “Reconstruction of random function distributions in single photon emission tomography problems using trigonometric polynomial approximation of exponential multiplier”, Inform. Primen., 5:3 (2011),  17–20  mathnet
2010
49. O. V. Shestakov, “Normal approximation for distribution of risk estimate for wavelet coefficients thresholding when using sample variance”, Inform. Primen., 4:4 (2010),  72–79  mathnet 13
50. A. V. Markin, O. V. Shestakov, “Asymptotic properties of risk estimate of wavelet-vaguelette coefficients thresholding in tomographic reconstruction problem”, Inform. Primen., 4:2 (2010),  36–45  mathnet 7
2009
51. O. V. Shestakov, “On stability of image reconstruction in the problems of emission tomography”, Inform. Primen., 3:3 (2009),  47–51  mathnet
52. V. G. Ushakov, O. V. Shestakov, “Reconstruction of probabilistic characteristics of random functions in spect problems”, Inform. Primen., 3:1 (2009),  29–33  mathnet 1
2008
53. A. V. Markin, O. V. Shestakov, “Elimination of ectopic beats fromheart tachogramusing robust estimates”, Inform. Primen., 2:2 (2008),  47–54  mathnet
54. Oleg Shestakov, “Fan-beam stochastic tomography”, Sistemy i Sredstva Inform., 2008, no. special issue,  62–77  mathnet
2006
55. V. G. Ushakov, O. V. Shestakov, “The application of wavelet expansions for solving the problems of computer tomography with a fan beam scanning schemes”, Sistemy i Sredstva Inform., 2006, no. special issue,  77–84  mathnet 1

Presentations in Math-Net.Ru
1. Probabilistic methods of tomographic images analysis and processing
O. V. Shestakov
Principle Seminar of the Department of Probability Theory, Moscow State University
September 12, 2012 16:45

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