1 citations · 3 across the 15 of their papers we have counts for
15 papers
Nonlinear Bias-Compensated Adaptive Filter and Its Application for Time-Series Prediction
Yi Peng, Haiquan Zhao, Jinhui Hu
Most existing nonlinear adaptive filtering algorithms only account for output noise, neglecting the fact that input noise is also prevalent in practice. Although the recently propo…
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…
Convergence analysis of accelerated algorithms via a mixed-order dynamical system for separable nonsmooth convex optimization
Geng-Hua Li, Hai-Yi Zhao, Xiangkai Sun
For a linear equality constrained convex optimization problem involving two objective functions with a ``nonsmooth" + ``nonsmooth" composite structure, we study two algorithms deri…
Robust distributed extended Kalman filter based on adaptive multi-kernel mixture maximum correntropy for non-Gaussian systems
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu +1
As one of the most advanced variants in the correntropy family, the multi-kernel correntropy criterion demonstrates superior accuracy in handling non-Gaussian noise, particularly w…
P-norm based Fractional-Order Robust Subband Adaptive Filtering Algorithm for Impulsive Noise and Noisy Input
Jianhong Ye, Haiquan Zhao, Yi Peng
Building upon the mean p-power error (MPE) criterion, the normalized subband p-norm (NSPN) algorithm demonstrates superior robustness in -stable noise environments ($1 < α\leq 2…
Distributed Cubature Kalman Filter based on MEEF with Adaptive Cauchy Kernel for State Estimation
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu
Nowadays, with the development of multi-sensor networks, the distributed cubature Kalman filter is one of the well-known existing schemes for state estimation, for which the influe…
State-of-charge estimation of lithium-ion batteries using a tree seed and genetic algorithm-optimized generalized mixture minimum error entropy-based square root cubature Kalman filter
Haiquan Zhao, Xiong Yin, Jinhui Hu
The cubature Kalman filter based on minimum error entropy (MEE-CKF) offers accurate and robust performance in state of charge (SOC) estimation. However, due to the inflexibility of…
Dynamic State Estimation of Power System Utilizing Cauchy Kernel-Based Maximum Mixture Correntropy UKF over Beluga Whale-Bat Optimization
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu
Non-Gaussian noise, outliers, sudden load changes, and bad measurement data are key factors that diminish the accuracy of dynamic state estimation in power systems. Additionally, u…
CKFNet: Neural Network Aided Cubature Kalman filtering
Jinhui Hu, Haiquan Zhao, Yi Peng
The cubature Kalman filter (CKF), while theoretically rigorous for nonlinear estimation, often suffers performance degradation due to model-environment mismatches in practice. To a…
Adaptive Robust Unscented Kalman Filter for Dynamic State Estimation of Power System
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu +1
Non-Gaussian noise and the uncertainty of noise distribution are the common factors that reduce accuracy in dynamic state estimation of power systems (PS). In addition, the optimal…
Diffusion Augmented Complex Maximum Total Correntropy Algorithm for Power System Frequency Estimation
Haiquan Zhao, Yi Peng, Jinsong Chen +1
Currently, adaptive filtering algorithms have been widely applied in frequency estimation for power systems. However, research on diffusion tasks remains insufficient. Existing dif…
Robust Square Root Unscented Kalman filter of graph signals
Jinhui Hu, Haiquan Zhao, Yi Peng
Considering the problem of nonlinear and non-gaussian filtering of the graph signal, in this paper, a robust square root unscented Kalman filter based on graph signal processing is…