Online dynamic mode decomposition for time-varying systems
Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow
analysis, and reduced-order modeling. In situations where a system is time varying, one …
analysis, and reduced-order modeling. In situations where a system is time varying, one …
State estimation in nonlinear system using sequential evolutionary filter
As a commonly encountered problem in the particle filters (PFs), the particle impoverishment
is caused partially by the reduction of particle diversity after resampling. In this paper, a …
is caused partially by the reduction of particle diversity after resampling. In this paper, a …
Extended and unscented filtering algorithms using one-step randomly delayed observations
A Hermoso-Carazo, J Linares-Pérez - Applied Mathematics and …, 2007 - Elsevier
In this paper, the least squares filtering problem is investigated for a class of nonlinear
discrete-time stochastic systems using observations with stochastic delays contaminated by …
discrete-time stochastic systems using observations with stochastic delays contaminated by …
Filtering and fault detection for nonlinear systems with polynomial approximation
This paper is concerned with polynomial filtering and fault detection problems for a class of
nonlinear systems subject to additive noises and faults. The nonlinear functions are …
nonlinear systems subject to additive noises and faults. The nonlinear functions are …
[HTML][HTML] Physics-Informed Neural Networks for Unmanned Aerial Vehicle System Estimation
The dynamic nature of quadrotor flight introduces significant uncertainty in system
parameters, such as thrust and drag factors. Consequently, operators grapple with …
parameters, such as thrust and drag factors. Consequently, operators grapple with …
Design Method of High-Order Kalman Filter for Strong Nonlinear System Based on Kronecker Product Transform
X Liu, C Wen, X Sun - Sensors, 2022 - mdpi.com
In this paper, a novel design idea of high-order Kalman filter based on Kronecker product
transform is proposed for a class of strong nonlinear stochastic dynamic systems. Firstly …
transform is proposed for a class of strong nonlinear stochastic dynamic systems. Firstly …
[HTML][HTML] Bilinear differential game for competitive advertising with stochastic disturbance and abrupt impact
W Tao, CK Zhang, L Yang - Expert Systems with Applications, 2023 - Elsevier
The estimated spending on online advertising worldwide will reach $520 billion during
2023, almost double compared with that in 2019. Due to the conjunction of huge …
2023, almost double compared with that in 2019. Due to the conjunction of huge …
Comments on “High-Speed Train Positioning Using Deep Kalman Filter With 5G NR Signals”
T Wen, H Jiang, C Roberts - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Recently, Ko et al.(2022) proposed a high-speed railway positioning scheme based on an
improved Kalman filter using 5G NR signals. Although the proposal was promising, our …
improved Kalman filter using 5G NR signals. Although the proposal was promising, our …
High-Speed Train Positioning Using Improved Extended Kalman Filter With 5G NR Signals
T Wen, H Jiang, B Cai, C Roberts - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the integration of 5G NR (New Radio) into railway systems, the demand for enhanced
positioning and trajectory tracking performance in High-Speed Train (HST) networks has …
positioning and trajectory tracking performance in High-Speed Train (HST) networks has …
Modeling the target extent with multiplicative noise
Extended target tracking deals with simultaneously tracking the shape and the kinematic
parameters of a target. In this work, we formulate the extended target tracking problem as a …
parameters of a target. In this work, we formulate the extended target tracking problem as a …