TIGP (SNHCC) -- Bias Compensation for Kernel Adaptive Filtering Algorithms
- LecturerProf. Ying-Ren Chien (Department of Electronic Engineering, National Taipei University of Technology)
Host: TIGP (SNHCC) - Time2026-03-16 (Mon.) 14:00 ~ 16:00
- LocationAuditorium 106 at IIS new Building
Abstract
This presentation introduces advanced Bias Compensation for Kernel Adaptive Filtering Algorithms to address the critical challenge of nonlinear system identification in "dual-threat" environments characterized by noisy regressors and impulsive output noise. To counteract the parameter estimation bias and system instability caused by these non-ideal effects, we propose two novel approaches: the Bias-Compensated Kernel Least Mean Square (BC-KLMS) algorithm, which explicitly corrects for input noise bias , and the Bias-Compensated Kernel Maximum Correntropy (BC-KMC) algorithm, which utilizes a modified cost function to simultaneously neutralize input noise bias and mitigate impulsive output outliers. Validated through complex time-series predictions, such as sunspot and