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Veretennikov Alexander Yurievich

Publications in Math-Net.Ru

  1. On higher order moments and rates of convergence for SDEs with switching

    Mosc. Math. J., 24:1 (2024),  107–124
  2. On strong law of large numbers for pairwise independent random variables

    Teor. Veroyatnost. i Primenen., 69:3 (2024),  427–438
  3. On improved bounds and conditions for the convergence of Markov chains

    Izv. RAN. Ser. Mat., 86:1 (2022),  98–133
  4. On pathwise uniqueness of solutions for multidimensional McKean–Vlasov equation

    Teor. Veroyatnost. i Primenen., 66:3 (2021),  581–588
  5. On weak solutions of highly degenerate SDEs

    Avtomat. i Telemekh., 2020, no. 3,  28–43
  6. On convergence rates for homogeneous Markov chains

    Dokl. RAN. Math. Inf. Proc. Upr., 490 (2020),  16–19
  7. On convergence of 1D Markov diffusions to heavy-tailed invariant density

    Mosc. Math. J., 19:1 (2019),  89–106
  8. On convergence rate for Erlang–Sevastyanov type models with infinitely many servers. In memory and to the 90th anniversary of A.D. Solovyev (06.09.1927–06.04.2001)

    Theory Stoch. Process., 22(38):1 (2017),  89–103
  9. On partial derivatives of multivariate Bernstein polynomials

    Mat. Tr., 18:2 (2015),  22–38
  10. On the rate of convergence to the stationary distribution in the single-server queuing systems

    Avtomat. i Telemekh., 2013, no. 10,  23–35
  11. On local mixing conditions for SDE approximations

    Teor. Veroyatnost. i Primenen., 57:1 (2012),  35–61
  12. On the rate of beta-mixing and convergence to a stationary distribution in continuous-time Erlang-type systems

    Probl. Peredachi Inf., 46:4 (2010),  122–129
  13. On stochastic averaging and mixing

    Theory Stoch. Process., 16(32):1 (2010),  111–129
  14. On mixing rate and convegence to stationary regime in discrete time Erlang problem

    Avtomat. i Telemekh., 2009, no. 12,  59–70
  15. On Continuous Time Ergodic Filters with Wrong Initial Data

    Teor. Veroyatnost. i Primenen., 53:2 (2008),  240–276
  16. On asymptotic information integral inequalities

    Theory Stoch. Process., 13(29):2 (2007),  294–307
  17. On subexponential mixing rate for Markov processes

    Teor. Veroyatnost. i Primenen., 49:1 (2004),  21–35
  18. On sde and semigroup approximations and large deviations

    Teor. Veroyatnost. i Primenen., 47:4 (2002),  772–780
  19. On polynomial mixing for SDEs with a gradient-type drift

    Teor. Veroyatnost. i Primenen., 45:1 (2000),  163–166
  20. On polynomial mixing and convergence rate for stochastic difference and differential equations

    Teor. Veroyatnost. i Primenen., 44:2 (1999),  312–327
  21. On large deviations in the averaging principle for stochastic differential equations with “complete dependence”

    Teor. Veroyatnost. i Primenen., 43:4 (1998),  765–767
  22. On large deviations for stochastic differentialequations with a small diffusion and averaging

    Teor. Veroyatnost. i Primenen., 43:2 (1998),  349–351
  23. Iterative Methods with Perturbationss in Ill-posed Problems

    Avtomat. i Telemekh., 1997, no. 4,  75–84
  24. On large deviations for diffusion processes with measurable coefficients

    Uspekhi Mat. Nauk, 50:5(305) (1995),  135–146
  25. On large deviations in the averaging principle for stochastic difference equations on a torus

    Trudy Mat. Inst. Steklov., 202 (1993),  33–41
  26. On large deviations for additive functionals of Markov processes. I

    Teor. Veroyatnost. i Primenen., 38:4 (1993),  758–774
  27. Ergodicity and mixing conditions for Markov processes in nonparametric filtering problems

    Avtomat. i Telemekh., 1991, no. 4,  36–45
  28. On large deviations in the averaging principle for stochastic differential equations with periodic coefficients. II

    Izv. Akad. Nauk SSSR Ser. Mat., 55:4 (1991),  691–715
  29. Large deviations for systems of Itô stochastic equations

    Teor. Veroyatnost. i Primenen., 36:4 (1991),  625–634
  30. The mixing rate and the averaging principle for recursive stochastic procedures

    Avtomat. i Telemekh., 1990, no. 6,  68–78
  31. On the averaging principle for systems of stochastic differential equations

    Mat. Sb., 181:2 (1990),  256–268
  32. On large deviations of the sojourn time for an ergodic process

    Teor. Veroyatnost. i Primenen., 35:2 (1990),  340–343
  33. On the optimal stabilization problem for random control processes with fast oscillating noise

    Avtomat. i Telemekh., 1989, no. 8,  75–80
  34. Conditions for hypo-ellipticity and estimates for the rate of mixing for stochastic differential equations

    Dokl. Akad. Nauk SSSR, 307:3 (1989),  524–526
  35. Stochastic calculus

    Itogi Nauki i Tekhniki. Ser. Sovrem. Probl. Mat. Fund. Napr., 45 (1989),  5–253
  36. On the rate of convergence of stochastically iterative procedures in ill-posed problems

    Avtomat. i Telemekh., 1988, no. 1,  72–77
  37. On rate of mixing and the averaging principle for hypoelliptic stochastic differential equations

    Izv. Akad. Nauk SSSR Ser. Mat., 52:5 (1988),  899–908
  38. The mean-square convergence of stochastic iterative processes in ill-posed problems

    Zh. Vychisl. Mat. Mat. Fiz., 28:6 (1988),  809–814
  39. Bounds for the Mixing Rate in the Theory of Stochastic Equations

    Teor. Veroyatnost. i Primenen., 32:2 (1987),  299–308
  40. Strong Solutions of Îto Stochastic Equations with Jumps

    Teor. Veroyatnost. i Primenen., 32:1 (1987),  159–163
  41. Regularization of ill-posed problems by stochastic iterative procedures in the mean

    Avtomat. i Telemekh., 1986, no. 10,  64–69
  42. On evaluation of the blending rate for autoregression processes

    Avtomat. i Telemekh., 1986, no. 3,  170–171
  43. On iterative methods in ill-posed problems with random errors

    Avtomat. i Telemekh., 1984, no. 12,  34–39
  44. Probabilistic problems in the theory of hypoellipticity

    Izv. Akad. Nauk SSSR Ser. Mat., 48:6 (1984),  1151–1170
  45. On the strong solutions of Itô–Volterra stochastic equations

    Teor. Veroyatnost. i Primenen., 29:1 (1984),  154–158
  46. Regularizing stopping rules under conditions of random errors

    Dokl. Akad. Nauk SSSR, 268:3 (1983),  521–524
  47. On stochastic equations with degenerate diffusion with respect to some of the variables

    Izv. Akad. Nauk SSSR Ser. Mat., 47:1 (1983),  189–196
  48. Approximation of ordinary differential equations by stochastic differential equations

    Mat. Zametki, 33:6 (1983),  929–932
  49. Inverse diffusion and direct derivation of stochastic liouville equations

    Mat. Zametki, 33:5 (1983),  773–780
  50. A probabilistic approach to hypoellipticity

    Uspekhi Mat. Nauk, 38:3(231) (1983),  113–125
  51. Parabolic equations and Itô's stochastic equations with coefficients discontinuous in the time variable

    Mat. Zametki, 31:4 (1982),  549–557
  52. On criteria for the existence of the strong solution of the stochastic equation

    Teor. Veroyatnost. i Primenen., 27:3 (1982),  417–424
  53. Ergodicity and invariance principle for multi-phase service systems

    Avtomat. i Telemekh., 1981, no. 7,  70–73
  54. Existence of an optimal strategy in control of a single dimensional diffusional process

    Avtomat. i Telemekh., 1981, no. 6,  28–34
  55. On the strong and weak solutions of one-dimensional stochastic equations with boundary conditions

    Teor. Veroyatnost. i Primenen., 26:4 (1981),  685–701
  56. On strong solutions and explicit formulas for solutions of stochastic integral equations

    Mat. Sb. (N.S.), 111(153):3 (1980),  434–452
  57. On the strong solutions of stochastic differential equations

    Teor. Veroyatnost. i Primenen., 24:2 (1979),  348–360
  58. On strong solutions of some stochastic equations

    Uspekhi Mat. Nauk, 33:5(203) (1978),  173–174
  59. The ergodicity of service systems with an infinite number of servomechanisms

    Mat. Zametki, 22:4 (1977),  561–569
  60. On explicit formulas for solutions of stochastic equations

    Mat. Sb. (N.S.), 100(142):2(6) (1976),  266–284

  61. Letter to the editors

    Teor. Veroyatnost. i Primenen., 43:4 (1998),  819
  62. Book review: «Algorithmes adaptifs et approximations stochastiques. Théorie et applications à l'identification, au traitement du signal et à la reconnaissance des formes» A. Benveniste, M. Metivier, P. Priouret

    Teor. Veroyatnost. i Primenen., 33:3 (1988),  633–634


© Steklov Math. Inst. of RAS, 2025