Books

• [B-02, URL] Kulikov G.Yu., Kulikova M.V. (2024) State Estimation for Nonlinear Continuous-Discrete Stochastic Systems: Numerical Aspects and Implementation Issues, Springer, Cham, 780 p. Hardcover ISBN: 978-3-031-61370-8, Softcover ISBN: 978-3-031-61373-9, eBook ISBN: 978-3-031-61371-5.
• [B-01] Semushin I.V., Tsyganova J.V., Kulikova M.V., Fatyanova O.A., Kondratyev A.E.  (2011) Adaptive systems of filtering, control and fault detection(in Russian) Ulyanovsk State University, Ulyanovsk, 298 p. ISBN 978-5-88866-399-8

Articles in Peer Reviewed Journal

The PDF preprints below are draft versions of the articles. They are presented here to give people an opportunity to check the relevance of the articles before purchasing the final articles from the publisher.

•  2025 
  [JP-84, DOI, SJRank] Kulikov G.Yu., Weiner R., Kulikova M.V. (2025) Hidden state estimation in stochastic integro-differential Amari model by adaptive singly diagonally implicit two-step peer triples with global error control. Digital Signal Processing, 158: 104941. Free access is provided for 50 days
•  2024 
  [JP-83, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2024) Maximum-correntropy-based sequential method for fast neural population activity reconstruction in the cortex from incomplete abnormally-disturbed noisy measurements. Communications in Nonlinear Science and Numerical Simulation, 139:108266.
• [JP-82, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2024) NIRK-based mixed-type accurate continuous-discrete Gaussian filters with deterministically sampled expectation and covariance for state estimation in continuous-time stochastic process models with discrete measurements. Journal of the Franklin Institute, 361(7):106768.
• [JP-81, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2024) Continuous-discrete derivative-free extended Kalman filter based on Euler-Maruyama and Itô-Taylor discretizations: Conventional and square-root implementations. European Journal of Control, 76: 100960.
• [JP-80, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2024) Euler-Maruyama-based data-driven state restoration and parameter adaptation in stochastic neural fields with finite signal transmission rate. IEEE Transactions on Information Theory, 70(6): 4571-4581.
• [JP-79, DOI, SJRank] Kulikova M.V., Taylor D.R., Kulikov G.Yu. (2024) Evolving efficiency of the BRICS markets. Economic Systems, 48(1): 101166. 
•  2023 
  [JP-78, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2023) On derivative-free extended Kalman filtering and its Matlab-oriented square-root implementations for state estimation in continuous-discrete nonlinear stochastic systems. European Journal of Control, 73: 100886.
• [JP-77, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2023) Data-driven parameter estimation in stochastic dynamic neural fields by state-space approach and continuous-discrete extended Kalman filtering. Digital Signal Processing, 136: 104010. 
• [JP-76, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2023) Accuracy analysis of numerical simulations and noisy data assimilations in two-dimensional stochastic neural fields with infinite signal transmission speed. Journal of the Franklin Institute, 360(1): 176-202.
•  2022 
  [JP-75, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2022) Universal MATLAB-based square-root solutions in the family of continuous-discrete Gaussian filters for state estimation in nonlinear stochastic dynamic systems. International Journal of Robust and Nonlinear Control, 32(15): 8227-8251.
• [JP-74, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2022) Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach. Digital Signal Processing, 128: 103619. 
• [JP-73, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2022) Overall hyperbolic-singular-value-decomposition-based square-root solutions in Kalman filters with deterministically sampled mean and covariance for state estimation in continuous-discrete nonlinear stochastic systems. European Journal of Control, 66: 100648.
• [JP-72, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2022) Continuous-discrete unscented Kalman filtering framework by MATLAB ODE solvers and square-root methods. Automatica, 142: 110396.
• [JP-71, DOI, SJRank] Lima P.M., Erlhagen W., Kulikova M.V., Kulikov G.Yu. (2022) Numerical solution of the stochastic neural field equation with applications to working memory. Physica A: Statistical Mechanics and its Applications, 596:127166.
• [JP-70, DOI, SJRank] Kulikova M.V., Lima P.M., Kulikov G.Yu. (2022) Sequential method for fast neural population activity reconstruction in the cortex from incomplete noisy measurements. Computers in Biology and Medicine, 141: 105103.
• [JP-69, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2022) Hyperbolic-SVD-based square-root unscented Kalman filters in continuous-discrete target tracking scenarios. IEEE Transactions on Automatic Control, 67(1): 366-373.
• [JP-68, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2022) Square-root filtering via covariance SVD factors in the accurate continuous-discrete extended-cubature Kalman filter. Applied Numerical Mathematics, 171:32-44.
•  2021 
  [JP-67, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2021) Square-root high-degree cubature Kalman filters for state estimation in nonlinear continuous-discrete stochastic systems. European Journal of Control, 59: 58-68.
• [JP-66, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2021) MATLAB-based general approach for square-root extended-unscented and fifth-degree cubature Kalman filtering methods. European Journal of Control, 59: 1-12.
• [JP-65, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2021) Itô-Taylor-based square-root unscented Kalman filtering methods for state estimation in nonlinear continuous-discrete stochastic systems. European Journal of Control, 58: 101-113.
• [JP-64, DOI, SJRank] Kulikova M.V., Tsyganova J.V., Kulikov G.Yu. (2021) SVD-based state and parameter estimation approach for generalized Kalman filtering with application to GARCH-in-Mean estimation. Journal of Computational and Applied Mathematics, 387: 112487.
• [JP-63, DOI, SJRank] Kulikov G.Yu., Lima P.M., Kulikova M.V. (2021) Numerical solution of the neural field equation in the presence of random disturbance. Journal of Computational and Applied Mathematics, 387: 112563. 
•  2020 
  [JP-62, DOI, SJRank] Kulikova M.V., Tsyganova J.V., Kulikov G.Yu. (2020) UD-based pairwise and MIMO Kalman-like filtering for estimation of econometric model structures. IEEE Transactions on Automatic Control, 65(10): 4472-4479.
• [JP-61, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2020) SVD-based factored-form Cubature Kalman Filtering for continuous-time stochastic systems with discrete measurements. Automatica, 120: 109110.
• [JP-60, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2020) Square-rooting approaches to accurate mixed-type continuous-discrete extended and fifth-degree cubature Kalman filters. IET Radar, Sonar & Navigation, 14(11): 1671-1680.
• [JP-59, DOI, SJRank] Kulikova M.V., Kulikov G. Yu. (2020) The J-orthogonal square-root MATLAB-based continuous-discrete unscented Kalman filtering method IFAC-PapersOnLine, 53(2): 4967-4972.
• [JP-58, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2020) A comparative study of Kalman-like filters for state estimation of turning aircraft in presence of glint noise IFAC-PapersOnLine, 53(2): 2335-2340.
• [JP-57, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2020) The J-orthogonal square-root Euler-Maruyama-based unscented Kalman filter for nonlinear stochastic systems IFAC-PapersOnLine, 53(2): 2361-2366.
• [JP-56, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2020) The J-orthogonal square-root fifth-degree cubature Kalman filtering method for nonlinear stochastic systems IFAC-PapersOnLine, 53(2): 4961-4966.
• [JP-55, DOI, SJRank] Kulikova M.V. (2020) On the stable Cholesky factorization-based method for the maximum correntropy criterion Kalman filtering IFAC-PapersOnLine, 53(2): 482-487. ArXiv
• [JP-54, DOI, SJRank] Tsyganova J.V., Kulikova M.V., Tsyganov A.V. (2020) A general approach for designing the MWGS-based information-form Kalman filtering methods. European Journal of Control, 56: 86-97.
• [JP-53, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2020) Hyperbolic-singular-value-decomposition-based square-root accurate continuous-discrete extended-unscented Kalman filters for estimating continuous-time stochastic models with discrete measurements. International Journal of Robust and Nonlinear Control, 30(5): 2033-2058.
• [JP-52, DOI, SJRank] Kulikova M.V. (2020) Chandrasekhar-based maximum correntropy Kalman filtering with the adaptive kernel size selection. IEEE Transactions on Automatic Control, 65(2): 741-748. Arxiv
• [JP-51, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2020) Square-root accurate continuous-discrete extended-unscented Kalman filtering methods with embedded orthogonal and J-orthogonal QR decompositions for estimation of nonlinear continuous-time stochastic models in radar tracking. Signal Processing, 166: 107253.
• [JP-50, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2020) NIRK-based Cholesky-factorized square-root accurate continuous-discrete unscented Kalman filters for state estimation in nonlinear continuous-time stochastic models with discrete measurements. Applied Numerical Mathematics, 147: 196-221.
• [JP-49, DOI, SJRank, PDF] Kulikova M.V. (2020) Sequential maximum correntropy Kalman filtering. Asian Journal of Control, 22(1):25-33.
•  2019 
  [JP-48, DOI, SJRank] Kulikova M.V. (2019) Square-root approach for Chandrasekhar-based maximum correntropy Kalman filtering . IEEE Signal Processing Letters, 26(12): 1803-1807.
• [JP-47, DOI, SJRank] Kulikova M.V. (2019) Hyperbolic SVD-based Kalman filtering for Chandrasekhar recursion. IET Control Theory & Applications, 13(10): 1525-1531.
• [JP-46, DOI, SJRank] Kulikova M.V. (2019) Factored-form Kalman-like implementations under maximum correntropy criterion. Signal Processing, 160: 328-338. ArXiv
• [JP-45, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2019) Numerical robustness of extended Kalman filtering based state estimation in ill-conditioned continuous-discrete nonlinear stochastic chemical systems. International Journal of Robust and Nonlinear Control, 29(5): 1377-1395.
• [JP-44, DOI, SJRank, PDF] Kulikov G.Yu., Taylor D.R., Kulikova M.V. (2019) A nonlinear Bayesian filtering approach to estimating adaptive market efficiency. Russian Journal of Numerical Analysis and Mathematical Modelling, 34(1): 31-42.
•  2018 
  [JP-43, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2018) Moore-Penrose-pseudo-inverse-based Kalman-like filtering methods for estimation of stiff continuous-discrete stochastic systems with ill-conditioned measurements. IET Control Theory & Applications, 12(16): 2205-2212.
• [JP-42, DOI, SJRank] Tsyganova Yu. V., Kulikova M.V. (2018) On modern array algorithms for optimal discrete filtering. Bulletin of the South Ural State University, Series: Mathematical Modelling, Programming and Computer Software, 11(4): 5-30.
• [JP-41, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2018) Stability analysis of extended, cubature and unscented Kalman filters for estimating stiff continuous-discrete stochastic systems. Automatica, 90: 91-97.
• [JP-40, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2018) Estimation of maneuvering target in the presence of non-Gaussian noise: A coordinated turn case study. Signal Processing, 145: 241-257.
• [JP-39, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2018) Practical implementation of extended Kalman filtering in chemical systems with sparse measurements. Russian Journal of Numerical Analysis and Mathematical Modelling, 33(1): 41-53.
•  2017 
  [JP-38, DOI, SJRank] Kulikova M.V., Tsyganova J.V. (2017) Improved discrete-time Kalman filtering within singular value decomposition. IET Control Theory & Applications, 11(15): 2412-2418. Arxiv
• [JP-37, DOI, SJRank] Kulikova M.V. (2017) Square-root algorithms for maximum correntropy estimation of linear discrete-time systems in presence of non-Gaussian noise. Systems and Control Letters, 108: 8-15. Arxiv
• [JP-36, DOI, SJRank] Tsyganova J.V., Kulikova M.V. (2017) SVD-based Kalman filter derivative computation. IEEE Transactions on Automatic Control, 62(9): 4869-4875. Arxiv
• [JP-35, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2017) Accurate state estimation of stiff continuous-time stochastic models in chemical and other engineering. Mathematics and Computers in Simulation, 142:62-81.
• [JP-34, DOI, SJRank] Kulikova M.V., Tsyganova J.V. (2017) The UD-based approach for designing pairwise Kalman filtering algorithms, IFAC-PapersOnLine, 50(1): 1619-1624.
• [JP-33, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2017) Do the contemporary cubature and unscented Kalman filtering methods outperform always the extended Kalman filter?  IFAC-PapersOnLine, 50(1): 3762-3767.
• [JP-32, URL] Kulikova M.V., Tsyganova J.V. (2017) Numerically stable Kalman filter implementations for estimating linear pairwise Markov models in the presence of Gaussian noise. Computational Technologies, 22(3): 45-60. (in Russian)
• [JP-31, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2017) Accurate continuous-discrete unscented Kalman filtering for estimation of nonlinear continuous-time stochastic models in radar tracking. Signal Processing, 139: 25-35.
• [JP-30, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2017) Square-root Kalman-like filters for estimation of stiff continuous-time stochastic systems with ill-conditioned measurements. IET Control Theory and Applications, 11(9): 1420-1425.
• [JP-29, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2017) Accurate state estimation in continuous-discrete stochastic state-space systems with nonlinear or nondifferentiable observations. IEEE Transactions on Automatic Control, 62(8): 4243-4250. 
• [JP-28, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2017) NIRK-based accurate continuous-discrete extended Kalman filters for estimating continuous-time stochastic target tracking models, Journal of Computational and Applied Mathematics, 316: 260-270.
• [JP-27, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2017) The continuous-discrete extended Kalman filter revisited. Russian Journal of Numerical Analysis and Mathematical Modelling, 32(1): 27-38.
• [JP-26, DOI, SJRank] Kulikova M.V. (2017) Gradient-based parameter estimation in pairwise linear Gaussian system, IEEE Transactions on Automatic Control, 62(3): 1511-1517.
• [JP-25, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2017) Accurate cubature and extended Kalman filtering methods for estimating continuous-time nonlinear stochastic systems with discrete measurements. Applied Numerical Mathematics, 111: 260-275.
•  2016 
  [JP-24, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2016) Estimating the state in stiff continuous-time stochastic systems within extended Kalman filtering, SIAM Journal on Scientific Computing, 38(6): A3565-A3588.
• [JP-23, URL] Kulikova M.V., Kulikov G.Yu. (2016) Numerical methods for nonlinear filtering of signals and measurements. Computational Technologies, 21(4): 64-98. (in Russian)
• [JP-22, DOI, SJRank] Kulikov G.Yu.,Kulikova M.V. (2016) The accurate continuous-discrete extended Kalman filter for radar tracking. IEEE Transactions on Signal Processing, 64(4): 948-958. 
• [JP-21, DOI, SJRank] Kulikova M.V., Tsyganova J.V. (2016) A unified square-root approach for the score and Fisher information matrix computation in linear dynamic systems, Mathematics and Computers in Simulation, 119: 128-141.
•  2015 
  [JP-20, DOI, SJRank] Kulikova M.V., Tsyganova J.V. (2015) Constructing numerically stable Kalman filter-based algorithms for gradient-based adaptive filtering, International Journal of Adaptive Control and Signal Processing, 29(11):1411-1426. Arxiv
• [JP-19, DOI, SJRank] Kulikova M.V., Tsyganova Yu.V. (2015) Differentiating matrix orthogonal transformations, Computational Mathematics and Mathematical Physics, 55(9): 1460-1473.
• [JP-18, DOI, SJRank] Kulikov G.Yu., Kulikova M.V. (2015) The accurate continuous-discrete extended Kalman filter for continuous-time stochastic systems, Russian Journal of Numerical Analysis and Mathematical Modelling, 30(4): 239-249.
• [JP-17, DOI, SJRank] Kulikov G.Yu., Kulikova M.V.  (2015) High-order accurate continuous-discrete extended Kalman filter for chemical engineering, European Journal of Control, 21:14-26. 
•  2014 
  [JP-16, DOI, SJRank] Kulikova M.V., Tsyganova J.V. (2014) A general approach to constructing parameter identification algorithms in the class of square root filters with orthogonal and J-orthogonal transformations, Automation and Remote Control, 75(8): 1402-1419.
• [JP-15, DOI, SJRank] Kulikova M.V., Kulikov G.Yu. (2014) Adaptive ODE solvers in extended Kalman filtering algorithms, Journal of Computational and Applied Mathematics, 262(5): 205-216.
• [JP-14, DOI, SJRank] Kulikov G. Yu., Kulikova M.V. (2014) Accurate numerical implementation of the continuous-discrete extended Kalman filter, IEEE Transactionson Automatic Control, 59(1): 273-279.
•  2013 
  [JP-13, DOI, SJRank] Tsyganova J.V., Kulikova M.V. (2013) State sensitivity evaluation within UD based array covariance filters, IEEE Transactions on Automatic Control, 58(11): 2944-2950. Arxiv
• [JP-12, DOI, SJRank] Kulikova M.V., Pacheco A. (2013) Kalman filter sensitivity evaluation with orthogonal and J-orthogonal transformations, IEEE Transactions on Automatic Control, 58(7): 1798-1804.
• [JP-11, DOI, SJRank, PDF] Kulikova M.V., Taylor D.R. (2013) Stochastic volatility models for exchange rates and their estimation using quasi-maximum-likelihood methods: an application to the South African Rand, Journal of Applied Statistics, 40(3): 495-507.
•  2012 
  [JP-10, DOI, SJRank] Tsyganova Yu.V., Kulikova M.V. (2012) On efficient parametric identification methods for linear discrete stochastic systems, Automation and Remote Control, 73(6): 962-975.
•  2011 
  [JP-09, DOI, SJRank] Kulikova M.V. (2011) Maximum likelihood estimation of linear stochastic systems in the class of sequential square-root orthogonal filtering methods, Automation and Remote Control, 72(4): 766-786.
•  2010 
  [JP-08, DOI, SJRank] Kulikova M.V., Taylor D.R. A conditionally heteroskedastic time series model for certain South African stock price returns, Investment Analysts Journal, 72: 43-52.
•  2009 
  [JP-07, DOI, SJRank] Kulikova M.V. (2009) Likelihood gradient evaluation using square-root covariance filters, IEEE Transactions on Automatic Control, 54(3): 646-651. Arxiv
• [JP-06, DOI, SJRank] Kulikova M.V. (2009) On scalarized calculation of the likelihood function in array square-root filtering algorithms, Automation and Remote Control, 70(5): 855-871.
• [JP-05, DOI, SJRank] Kulikova M.V. (2009) Maximum likelihood estimation via the extended covariance and combined square-root filters, Mathematicsand Computers in Simulation, 79(5): 1641-1657.
•  2006 
  [JP-04, DOI, SJRank] Kulikova M.V., Semoushin I.V. (2006) Score evaluation within the extended square-root information filter, Lecture Notes in Computer Science, 3991: 473-481.
•  2005 
  [JP-03, URL, SJRank] Kulikova M.V., Semoushin I.V. (2005) On the evaluation of log likelihood gradient for Gaussian signals, International Journal of Applied Mathematicsand Statistics, 3(5): 1-14.
•  2003 
  [JP-02, DOI, SJRank] Kulikova M.V. (2003) On effective computation of the logarithm of the likelihood ratio function for Gaussian signals, Lecture Notes in Computer Science, 2658: 427-435.
• [JP-01, DOI, SJRank] Semoushin I.V., Tsyganova J.V., Kulikova M.V. (2003) Fault point detection with the bank of competitive Kalman filters, Lecture Notes in Computer Science, 2658: 417-426.

Conference Proceedings

• [CP-27, DOI] Kulikova M.V., Lima P.M., Kulikov G.Yu. (2022) Accurate Itô-Taylor-discretization-based state estimation in stochastic neural field equations with infinite signal transmission rate, Proceedings of European Control Conference, London, United Kingdom, pp. 1436-1441.
• [CP-26, DOI] Kulikova M.V., Lima P.M., Kulikov G.Yu. (2022) Pattern recognition facilities of extended Kalman filtering in stochastic neural fields, Proceedings of European Control Conference, London, United Kingdom, pp. 1061-1066.
• [CP-25, DOI] Kulikova M.V., Lima P.M., Kulikov G.Yu. (2021) Reconstruction of hidden states in stochastic neural field equations with infinite signal transmission rate, Proceedings of the 25th International Conference on System Theory, Control and Computing, Iasi, Romania, pp. 358-365.
• [CP-24, DOI] Kulikova M.V., Taylor D.R., Kulikov G.Yu. (2021) Estimating a degree of evolving market efficiency: How efficient is the Romanian stock market? Proceedings of the 25th International Conference on System Theory, Control and Computing, Iasi, Romania, pp. 665-670.
• [CP-23, DOI] Kulikov G.Yu., Kulikova M.V. (2021) Self-adaptive MATLAB-based Gauss-Hermite quadrature filter for state estimation in nonlinear continuous-discrete stochastic systems, Proceedings of European Control Conference, Rotterdam, Netherlands, pp. 848-853.
• [CP-22, DOI] Lima P.M., Erlhagen W., Kulikov G.Yu., Kulikova M.V. (2021) Mathematical modeling of working memory in the presence of random disturbance using neural field equations, Proceedings of V International Conference "Modeling of Nonlinear Processes and Systems" (MNPS-2020). EPJ Web of Conferences 248, 01021. Moscow, Russia.  
• [CP-21, DOI] Kulikova M.V., Kulikov G.Yu., Lima P.M. (2020) Accuracy study in numerical simulations to stochastic neural field equations, Proceedings of the 24th International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 254-261.  
• [CP-20, DOI] Kulikova M.V., Tsyganova J.V. (2020) Numerically robust maximum correntropy criterion Kalman filtering using the UD covariance factorization approach, Proceedings of European Control Conference, Saint Petersburg, Russia, pp. 1383-1388.
• [CP-19, DOI] Kulikov G.Yu., Kulikova M.V. (2019) The J-orthogonal square-root NIRK-based Extended-Unscented Kalman filter for nonlinear continuous-discrete stochastic systems. In: Proceedings of the 58-th IEEE Conference on Decision and Control, IEEE-CDC 2019. Nice, France, pp. 373-378.
• [CP-18, DOI] Kulikova M.V., Kulikov G.Yu., Lima P.M. (2019) Effective numerical solution to two-dimensional stochastic neural field equations, Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 650-655.  
• [CP-17, DOI] Kulikov G.Yu., Kulikova M.V., Lima P.M. (2019) Numerical simulation of neural fields with finite transmission speed and random disturbance, Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 644-649.  
• [CP-16, DOI] Kulikov G.Yu., Kulikova M.V. (2019) SVD-based factored-form extended Kalman filters for state estimation in nonlinear continuous-discrete stochastic systems, Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 137-142.  
• [CP-15, DOI] Kulikova M.V. (2019) One-step condensed forms for square-root maximum correntropy criterion Kalman filtering, Proceedings of the 23rd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 13-18. Arxiv
• [CP-14, DOI] Tsyganova J.V., Kulikova M.V., Tsyganov A.V. (2019) Some new array information formulations of the UD-based Kalman filter, Proceedings of European Control Conference, Naples, Italy, pp. 1872-1877.
• [CP-13, DOI] Kulikova M.V. (2018) Numerically robust SVD-based Kalman filter implementations, Proceedings of the 22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 170-175.
• [CP-12, DOI] Kulikova M.V., Tsyganova J.V., Kulikov G.Yu. (2018) SVD-based state estimation of pairwise Markov models with application in econometrics, Proceedings of the 22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 188-193.
• [CP-11, DOI] Kulikov G.Yu., Kulikova M.V. (2018) Numerical stability of EKF-based software sensors in chemical engineering: A Van Der Vusse reaction case study, Proceedings of the 22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 286-291.
• [CP-10, DOI] Kulikov G.Yu., Kulikova M.V. (2018) Accuracy issues in Kalman filtering state estimation of stiff continuous-discrete stochastic models arisen in engineering research, Proceedings of the 22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, pp. 800-805.
• [CP-09, DOI] Kulikova M.V., Kulikov G.Yu. (2016) On computational robustness of accurate continuous-discrete unscented Kalman filtering for target tracking models, Proceedings of European Control Conference, Aalborg, Denmark, pp. 1129-1134.
• [CP-08, DOI] Kulikov G.Yu., Kulikova M.V. (2016) Accurate continuous-discrete extended Kalman filtering for stiff continuous-time stochastic models in chemical engineering, Proceedings of European Control Conference, Aalborg, Denmark, pp. 1728-1733.
• [CP-07, DOI] Kulikova M.V., Tsyganova J.V., Semushin I.V. (2016) Adaptive wave filtering for marine vessels within UD-based algorithms, Proceedings of European Control Conference, Aalborg, Denmark, pp. 807-812.
• [CP-06, DOI] Semushin I.V., Tsyganova J.V., Kulikova M.V., Tsyganov A., Peskov A. (2016) Identification of human body daily temperature dynamics via minimum state prediction error method, Proceedings of European Control Conference, Aalborg, Denmark, pp. 2429-2434. 
  [CP-05, DOI] Kulikova M.V. (2015) Square-root adaptive wave filtering for marine vessels. Proceedings of European Control Conference, Linz, Austria, pp. 3143-3148.
• [CP-04, DOI] Kulikova M.V., Kulikov G.Yu. (2015) A mixed-type accurate continuous-discrete extended-unscented Kalman filter for target tracking. Proceedings of European Control Conference, Linz, Austria, pp. 2824-2829.
• [CP-03, DOI] Kulikov G.Yu., Kulikova M.V. (2015) State estimation in chemical systems with infrequent measurements. Proceedings of European Control Conference, Linz, Austria, pp. 2688-2693.
  [CP-02, DOI] Kulikov G.Yu., Kulikova M.V. (2014) Accurate state estimation in the Van der Vusse reaction. Proceedings of the IEEE Conference on Control Applications, Antibes, France, pp. 759-764.
  [CP-01, DOI] Kulikova M.V., Kulikov G.Yu. (2013) Square-root accurate continuous-discrete extended Kalman filter for target tracking. Proceedings of the IEEE Conference on Decision and Control, Florence, Italy, pp. 7785-7790.