Error-distribution-free kernel extreme learning machine for traffic flow forecasting
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 …
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 …
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 …
estimation area with the Gaussian white noise hypothesis. The actual sensor noise is often …
Broad learning system based on maximum correntropy criterion
As an effective and efficient discriminative learning method, broad learning system (BLS)
has received increasing attention due to its outstanding performance in various regression …
has received increasing attention due to its outstanding performance in various regression …
Mixture correntropy-based kernel extreme learning machines
Kernel-based extreme learning machine (KELM), as a natural extension of ELM to kernel
learning, has achieved outstanding performance in addressing various regression and …
learning, has achieved outstanding performance in addressing various regression and …
Quantized minimum error entropy with fiducial points for robust regression
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 …
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 …
Traditional Kalman filter is prone to performance degradation and even filtering divergence …
Convergence analysis of a fixed point algorithm under maximum complex correntropy criterion
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 …
(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 …
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 …
Kalman filter (CEEVBKF) is proposed to suppress outlier noise and estimate the unknown …