Error-distribution-free kernel extreme learning machine for traffic flow forecasting

K Wu, C Xu, J Yan, F Wang, Z Lin, T Zhou - Engineering Applications of …, 2023 - Elsevier
Traffic flow modeling plays a crucial role in intelligent transportation systems, which is of vital
significance for mitigating traffic congestion and reducing carbon emissions. Owing to the …

Broad learning system based on the quantized minimum error entropy criterion

S Zhang, Z Liu, CLP Chen - Science China Information Sciences, 2022 - Springer
The broad learning system (BLS) based on the minimum mean square error (MMSE)
criterion can achieve outstanding performance without spending too much time in various …

[HTML][HTML] Centered error entropy-based sigma-point Kalman filter for spacecraft state estimation with non-Gaussian noise

B Yang, H Huang, L Cao - Space: Science & Technology, 2022 - spj.science.org
The classical sigma-point Kalman filter (SPKF) is widely used in a spacecraft state
estimation area with the Gaussian white noise hypothesis. The actual sensor noise is often …

Broad learning system based on maximum correntropy criterion

Y Zheng, B Chen, S Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As an effective and efficient discriminative learning method, broad learning system (BLS)
has received increasing attention due to its outstanding performance in various regression …

Mixture correntropy-based kernel extreme learning machines

Y Zheng, B Chen, S Wang, W Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Kernel-based extreme learning machine (KELM), as a natural extension of ELM to kernel
learning, has achieved outstanding performance in addressing various regression and …

Quantized minimum error entropy with fiducial points for robust regression

Y Zheng, S Wang, B Chen - Neural Networks, 2023 - Elsevier
Minimum error entropy with fiducial points (MEEF) has received a lot of attention, due to its
outstanding performance to curb the negative influence caused by non-Gaussian noises in …

Centered error entropy Kalman filter with application to satellite attitude determination

B Yang, L Cao, D Ran, B Xiao - Transactions of the Institute …, 2021 - journals.sagepub.com
Due to unavoidable factors, heavy-tailed noise appears in satellite attitude estimation.
Traditional Kalman filter is prone to performance degradation and even filtering divergence …

Convergence analysis of a fixed point algorithm under maximum complex correntropy criterion

G Qian, S Wang, L Wang, S Duan - IEEE Signal Processing …, 2018 - ieeexplore.ieee.org
With the emergence of complex correntropy, the maximum complex correntropy criterion
(MCCC) has been applied to the complex-domain adaptive filtering. The MCCC uses the …

Fixed-point generalized maximum correntropy: Convergence analysis and convex combination algorithms

J Zhao, H Zhang, G Wang - Signal Processing, 2019 - Elsevier
Compared with the MSE criterion, the generalized maximum correntropy (GMC) criterion
shows a better robustness against impulsive noise. Some gradient based GMC adaptive …

Centered error entropy-based variational Bayesian adaptive and robust Kalman filter

B Yang, B Du, N Li, S Li, Z Shi - IEEE Transactions on Circuits …, 2022 - ieeexplore.ieee.org
In this brief, a centered error entropy based variational Bayesian adaptive and robust
Kalman filter (CEEVBKF) is proposed to suppress outlier noise and estimate the unknown …