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 two gradient-based adaptive algorithms, called the least mean M
estimate and the transform domain least mean M-estimate (TLMM) algorithms, for robust …

This paper studies the problem of robust adaptive filtering in impulsive noise environment
using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust …

In this brief, an affine-projection-like M-estimate (APLM) algorithm is proposed for robust
adaptive filtering. To eliminate the adverse effects of impulsive noise in case of the impulse …

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 …

In this paper, three Lorentzian based robust adaptive algorithms are proposed for identifying
systems in presence of impulsive noise. The first algorithm called Lorentzian adaptive …

This brief proposes a novel variable step-size affine projection sign algorithm (APSA), which
is characterized by its robustness against impulsive noises. To obtain a step size …

This brief introduces the concept of a step-size scaler by investigating and modifying the
tanh cost function for adaptive filtering with impulsive measurement noise. The step-size …

In practical applications, the impulse responses (IRs) of some network echo paths are
blocksparse (BS), while the traditional proportionate and zero attraction algorithms do not …

In this brief, a robust shrinkage normalized sign (RSHNS) algorithm is presented, which
uses an optimal step size by minimizing the energy of the noise-free a posteriori error signal …