Constraint-Forcing Recursive Generalized Maximum Correntropy Algorithm with Forgetting Factor for Adaptive Filtering - Li, Wenyue; Zhao, Ji; Li, Qiang; Tang, Lingli; Zhang, Hongbin (Proceedings - International Conference on Parallel and Distributed Systems, 2023)
In this paper, jointly with the exponential weighted generalized maximum correntropy (GMC) criterion and the linear constraint framework, we derive a recursive constrained adaptive filtering algorithm named recursive constrained GMC with forgetting factor (FF-RCGMC). In addition, due to a lack of constraint information during the learning process, FF-RCGMC will diverge or even fail to work after some iterations. Therefore, we propose a more stable version by introducing a constraint-forcing strategy into FF-RCGMC and call this robust type as constraint-forcing FF-RCGMC (CFFF-RCGMC). Some simulation results in system identification under non-Gaussian noisy environments validate the effectiveness of CFFF-RCGMC.