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 …

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 …

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 …

The maximum correntropy criterion (MCC) algorithm with constant kernel width leads to a
tradeoff problem in terms of convergence rate and steady-state misalignment. Thus, this brief …

This paper deals with the use of least mean squares (LMS, NLMS) and recursive least
squares (RLS) algorithms for total harmonic distortion (THD) reduction using shunt active …

This work develops robust diffusion recursive least-squares algorithms to mitigate the
performance degradation often experienced in networks of agents in the presence of …

In recent years, the hyperbolic family of adaptive algorithms have been widely used to
combat impulsive noise. The novel exponential hyperbolic sine adaptive filters (EHSAF) and …

In this paper, a new framework of cost function for designing robust adaptive filtering
algorithms is developed. This new cost framework, called sigmoid cost function, results 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 …

This paper presents a family of robust set-membership normalized subband adaptive
filtering (RSM-NSAF) algorithms for acoustic echo cancellation (AEC). By using a new robust …