Zobrazeno 1 - 10
of 145
pro vyhledávání: '"Kulikova, Maria V."'
Publikováno v:
Economic Systems, 48(1): 101166, 2024
This paper investigates a time-varying version of weak-form market efficiency in the BRICS countries. A moving window test for sample autocorrelations is applied alongside a Kalman filter approach to recover the hidden dynamics of the market efficien
Externí odkaz:
http://arxiv.org/abs/2403.05233
Publikováno v:
European Journal of Control, 76: 100960, 2024
In this paper, we continue to study the derivative-free extended Kalman filtering (DF-EKF) framework for state estimation of continuous-discrete nonlinear stochastic systems. Having considered the Euler-Maruyama and It\^{o}-Taylor discretization sche
Externí odkaz:
http://arxiv.org/abs/2403.04448
Publikováno v:
IEEE Transactions on Automatic Control, 65(10): 4472-4479, 2020
One of the modern research lines in econometrics studies focuses on translating a wide variety of structural econometric models into their state-space form, which allows for efficient unknown dynamic system state and parameter estimations by the Kalm
Externí odkaz:
http://arxiv.org/abs/2402.11560
Publikováno v:
Automatica, 120: 109110, 2020
In this paper, a singular value decomposition (SVD) approach is developed for implementing the cubature Kalman filter. The discussed estimator is one of the most popular and widely used method for solving nonlinear Bayesian filtering problem in pract
Externí odkaz:
http://arxiv.org/abs/2402.11555
Publikováno v:
Proceedings of European Control Conference, London, United Kingdom, pp. 1061-1066, 2022
In mathematical neuroscience, a special interest is paid to a working memory mechanism in the neural tissue modeled by the Dynamic Neural Field (DNF) in the presence of model uncertainties. The working memory facility implies that the neurons' activi
Externí odkaz:
http://arxiv.org/abs/2402.11551
Publikováno v:
European Journal of Control, 73: 100886, 2023
Recent research in nonlinear filtering and signal processing has suggested an efficient derivative-free Extended Kalman filter (EKF) designed for discrete-time stochastic systems. Such approach, however, has failed to address the estimation problem f
Externí odkaz:
http://arxiv.org/abs/2402.11309
Publikováno v:
European Journal of Control, 59: 1-12, 2021
A stable square-root approach has been recently proposed for the unscented Kalman filter (UKF) and fifth-degree cubature Kalman filter (5D-CKF) as well as for the mixed-type methods consisting of the extended Kalman filter (EKF) time update and the U
Externí odkaz:
http://arxiv.org/abs/2312.02846
Publikováno v:
Applied Numerical Mathematics, 171:32-44, 2022
This paper continues our research devoted to an accurate nonlinear Bayesian filters' design. Our solution implies numerical methods for solving ordinary differential equations (ODE) when propagating the mean and error covariance of the dynamic state.
Externí odkaz:
http://arxiv.org/abs/2311.11299
Autor:
Kulikova, Maria V.
Publikováno v:
Signal Processing, 160: 328-338, 2019
The maximum correntropy criterion (MCC) methodology is recognized to be a robust filtering strategy with respect to outliers and shown to outperform the classical Kalman filter (KF) for estimation accuracy in the presence of non-Gaussian noise. Howev
Externí odkaz:
http://arxiv.org/abs/2311.02440
Autor:
Kulikova, Maria V.
Publikováno v:
IFAC-PapersOnLine, 53(2): 482-487, 2020
This paper continues the research devoted to the design of numerically stable square-root implementations for the maximum correntropy criterion Kalman filtering (MCC-KF). In contrast to the previously obtained results, here we reveal the first robust
Externí odkaz:
http://arxiv.org/abs/2311.02438