In this paper, a correntropy-based evolving fuzzy neural system (correntropy-EFNS) is proposed for approximation of nonlinear systems. Different from the commonly used meansquare error criterion, correntropy has a strong outliers rejection ability through capturing the higher moments of the error distribution. Considering the merits of correntropy, this paper brings contributions to build EFNS ...

Within the statistical learning framework, this paper studies the regression model associated with the correntropy induced losses. The correntropy, as a similarity measure, has been frequently employed in signal processing and pattern recognition. Motivated by its empirical successes, this paper aims at presenting some theoretical understanding towards the maximum correntropy criterion in regre...

Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises....

As a similarity measure, correntropy has been increasingly employed in machine learning research. While numerous experimental results have shown the effectiveness of correntropy based methods, the theoretical analysis in this area is still poorly understood. In this paper, we propose a novel semi-supervised algorithm under the maximum correntropy criterion, and present an elaborate error analys...

As a well-established adaptation criterion, the maximum correntropy criterion (MCC) has been receiving increasing attention due to its robust against outliers. In this paper, a new complex recursive maximum correntropy (CRMC) algorithm without any priori information on the noise characteristics, is proposed under the MCC. The proposed algorithm is useful for adaptive beamforming, when the desir...

1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710049, China 2. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China 3. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611 USA Abstract—As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attent...

To address sparse system identification problem in non-Gaussian impulsive noise environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm with sparse penalty constraints is proposed to combat impulsive-inducing instability. Specifically, a recursive algorithm based on the generalized correntropy with a forgetting factor of error is developed to improve the performan...