13 citations · 28 across the 12 of their papers we have counts for
4 papers · 1 filter
Outlier-Robust unscented Kalman filter based on generalized correntropy induced
Jinhui Hu, Haiquan Zhao, Yi Peng
Conventional Kalman filtering (KF) approaches exhibit significant limitations in addressing nonlinear state estimation problems contaminated by non-Gaussian noise disturbances. To…
Decentralized Variational Bayesian UKF with Maximum Generalized Student's t-kernel Correntropy for Wide-Area Power System state estimation
Jinhui Hu, Haiquan Zhao, Yi Peng
A Conventional centralized state estimators exhibit limited robustness in large-scale grids and face practical deployment hurdles. To overcome these challenges, this paper proposes…
Broad learning system with robust adaptive kernel
Haiquan Zhao, Jinhui Hu, Xin Lua
For the performance degradation problem of broad learning system (BLS) in non-Gaussian noise environment, the variant of BLS based on M-estimator shows good robust performance. How…
A Fast Robust Adaptive filter using Improved Data-Reuse Method
Yi Peng, Haiquan Zhao, Jinhui Hu
Adaptive filter in complex scenarios demands algorithms that integrate fast convergence, low complexity, and robust performance under diverse noise conditions. To address this chal…