To enhance the robustness and reduce the steady-state error under impulsive noise
environment, this brief proposes an augmented complex generalized modified Blake …

In the context of channel estimation amid non-Gaussian impulse noise, traditional non-
kernel-space methods face challenges of divergence, while many kernel-space methods fail …

The sparsity-aware recursive least squares (RLS) algorithms have been designed to impose
norm or-norm) constraint on RLS iteration to exploit sparsity contained in the target system …

When nonlinear loads are introduced to a distribution system, various power quality
challenges emerge, such as load unbalance, harmonic distortion, and reactive power …

To improve the robust characteristic and filtering accuracy of the traditional adaptive filtering
algorithms (AFAs) under censored regression (CR) model in impulsive interference …

Constrained adaptive filtering has developed rapidly in recent years. The constrained least
lncosh (CLL) algorithm has good performance in heavy-tailed impulsive noise …

The augmented affine projection algorithm (AAPA) has a faster convergence rate than the
augmented complex-valued LMS (ACLMS) algorithm for correlated inputs. However, they …

To address the problems of time variations and high interferences in continuous-wave mud
pulse telemetry channels, a widely linear recursive least squares decision feedback …

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

The Gaussian kernel function-based Minimum Error Entropy (MEE) criterion is effective for
special types non-Gaussian noise. However, non-Gaussian noise distributions and shapes …