9 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…
Online Censoring-Based Widely Linear Total Least lncosh Method for Improved Power System Frequency Estimation
Haiquan Zhao, Kaleab Derbew Abebe, Yi Peng
Recently, under the presumption of a noise-free input, the augmented complex least lncosh (ACLlncosh) method was introduced for a power system frequency estimate and showed robust…
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…
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…
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…