Non-Gaussian randomness widely exists in complex dynamical systems, in which the
traditional mean-variance index cannot fully reflect the systematic characteristics. To …

This brief proposes a recursive constrained sine second-order error promoting adaptive
(RCSSOEPA) algorithm. Compared with classical recursive method, the RCSSOEPA …

As a robust online learning approach, adaptive filtering based on correntropy has attracted
more attentions. Recently, researchers have made efforts to develop complex correntropy to …

Data selection can be used in conjunction with adaptive filtering algorithms to avoid
unnecessary weight updating and thereby reduce computational overhead. This paper …

The affine projection sign algorithm (APSA) is widely used to alleviate the impact of
impulsive noise on weight updates for adaptive filters. When using the conventional APSA …

As a powerful tool, the minimum error entropy (MEE) criterion has aroused extensive
attention within the field of adaptive filtering recently. However, most MEE-based methods …

In this brief, a robust constrained filtering algorithm is proposed by introducing a novel cost
function framework into the constrained adaptive algorithm. The proposed algorithm is …

The Hammerstein model is a crucial model frequently employed in the field of signal
processing. This paper focuses on the widely-linear (WL) complex-valued adaptive filtering …

In the field of nonlinear signal processing, Volterra filter is generally used as an effective
tool. The utilization of the augmented model can make the filter maintain its merit in both …

For system identification under impulsive-noise environments, the gradient-based
generalized maximum correntropy criterion (GB-GMCC) algorithm can achieve a desirable …