An exhaustive review of adaptive signal processing schemes which are robust, sparsity-
aware and robust as well as sparsity-aware has been carried out in this paper. Conventional …

Abstract The Unscented Kalman filter (UKF) based on maximum correntropy criterion (MCC)
is robust to heavy-tailed non-Gaussian noise. However, the approximate linear …

In this paper, we investigate the state estimation problem of nonlinear systems with non-
Gaussian measurement noise. Based on a newly defined cost function which is obtained by …

Currently, the generalized maximum correntropy criterion (GMCC) is extensively used in
adaptive filtering arithmetic to handle generalized Gaussian noise. However, when the input …

It is valuable and meaningful to suppress impulsive noise in system identification. Existing
algorithms usually only consider impulsive noise with small frequency and amplitude …

The maximum correntropy unscented Kalman filter (MCUKF) is a newly proposed non-linear
state estimation algorithm that is robust to non-Gaussian noise. In this paper, we propose …

Accurate knowledge of transmission line parameters is essential for a variety of power
system monitoring, protection, and control applications. The use of phasor measurement unit …

In this study, we consider the parameter estimation problem for an errors-in-variables (EIV)
model with impulse noise. New adaptive filtering, called the maximum total generalized …

This work revisits the problem of distributed adaptive filtering in multi-agent sensor networks.
In contrast to classical approaches, the formulation relaxes the Gaussian assumption on the …

In this brief, an improved maximum correntropy criterion subband adaptive filter (MCC-SAF)
algorithm is presented, which has excellent performance for alleviating the effect of …