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 …

As an effective and efficient discriminative learning method, broad learning system (BLS)
has received increasing attention due to its outstanding performance in various regression …

In this paper, a robust adaptive algorithm, called recursive minimum error entropy, is derived
under the minimum error entropy criterion. The new algorithm can perform robustly under …

This paper proposes a unified sparsity-aware robust recursive least-squares RLS (S-RRLS)
algorithm for the identification of sparse systems under impulsive noise. The proposed …

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 dichotomous coordinate descent (DCD) algorithm has been successfully used for
significant reduction in the complexity of recursive least squares (RLS) algorithms. In this …

Gaussian kernel adaptive filters (GKAFs) have been successfully applied in functional
approximation. The kernel bandwidth for GKAFs not only impacts on the smoothness of …

In this brief, a new least mean square (LMS) adaptive filtering algorithm based on Amari-
Alpha information theoretic divergence is proposed which is named as Amari-Alpha LMS …

Localization has been a well-investigated problem in the past decade for several networks
and is one of the most celebrated applications of adaptive signal processing. However …

In this paper, we propose a modified version of exponential cost function to improve the
stability of adaptive algorithm, where the recursive algorithm is based on the Dawson …