In this brief, a robust and sparse recursive adaptive filtering algorithm, called convex regularized recursive maximum correntropy (CR-RMC), is derived by adding a general convex regularization penalty term to the maximum correntropy criterion (MCC). An approximate expression for automatically selecting the regularization parameter is also introduced. Simulation results show that the CR-RMC can...

Zongze Wu 1 , Jiahao Shi 1 , Xie Zhang 1 , Wentao Ma 2 , Badong Chen 2* , Senior Member, IEEE 1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China 2. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, China * Fax: 86-29-82668672,Tel:86-29-82668802 ext. 8009, [email protected] Abstract—I...

—Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive noises, the performance of KF will deteriorate seriously. To improve the robustness of KF against impulsive noises, we propose in ...

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the cl...

Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher-order statistical moments in nonGaussian noise environments. Although it has been used with complex data, some adaptations were then necessary without deriving a generic form so that similarities between complex random variables can be aggregated. This paper presents a novel probabilistic interpretation ...

Xi Liu, Badong Chena∗, Bin Xu, Zongze Wu, and Paul Honeine School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China; School of Automation, Northwestern Polytechnical University, Xi’an, China; School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China; the Normandie Univ, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, Rouen, ...

Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher-order statistical moments in nonGaussian noise environments. Although correntropy has been used with complex data, no theoretical study was pursued to elucidate its properties, nor how to best use it for optimization . This paper presents a probabilistic interpretation for correntropy using complex-value...