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 …

This paper proposes the use of a least mean fourth (LMF)-based algorithm for single-stage
three-phase grid-integrated solar photovoltaic (SPV) system. It consists of an SPV array …

The hyperbolic cosine function with high-order errors can be utilized to improve the accuracy
of adaptive filters. However, when initial weight errors are large, the hyperbolic cosine …

We introduce a novel family of adaptive filtering algorithms based on a relative logarithmic
cost inspired by the “competitive methods” from the online learning literature. The …

In the case where the measurement noise involves impulsive interference, distributed
estimation algorithms based on the mean-square error (MSE) criterion may suffer from …

The conventional logarithm cost-based adaptive filters, eg, the least mean logarithmic
square (LMLS) algorithm, cannot combat impulsive noises at the filtering process. To …

The least mean fourth algorithm has several stability problems. Its stability depends on the
variance and distribution type of the adaptive filter input, the noise variance, and the …

The quality of power delivered has significantly decreased as distributed energy resources
are increasingly incorporated into the current electricity grid. Three-phase voltage source …

Adaptive filtering algorithms developed by using the negated kurtosis of the error signal as
cost function can obtain good performance in some types of sub-Gaussian noise …

This paper proposes several efficient and less complex signal conditioning algorithms for
brain signal enhancement in remote healthcare monitoring applications. In clinical …