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, we propose and analyze the sparsity-aware sign subband adaptive filtering
with individual weighting factors (S-IWF-SSAF) algorithm, and consider its application in …

This paper proposes a novel spline adaptive filtering (SAF) algorithm for nonlinear system
identification under impulsive noise environments. This algorithm combines the logarithmic …

There are different strategies to improve the overall performance of the recursive least-
squares (RLS) adaptive filter. In this letter, we focus on the data-reuse approach, aiming to …

Functional link artificial neural network (FLANN) has received much attention due to its wide
applicability. The Van der Pol-Duffing oscillator (VdPDO)-based nonlinear systems, which …

In this work, we present an energy-efficient distributed learning framework using coarsely
quantized signals for Internet of Things (IoT) networks. In particular, we develop a distributed …

This paper presents a new least mean square (LMS) algorithm with defining hyperbolic
secant cost function. Then, the detailed analysis is conducted to reveal the behavior of the …

The normalized subband adaptive filter (NSAF) has a faster convergence rate than the
NLMS adaptive filter when the input signal is correlated. Recently some sparsity-aware …

Abstract Self-interference (SI) cancellation (SIC) is the key technology for achieving full-
duplex (FD) communications in underwater acoustic systems. In practice, SI channels are …

The exponential functional link network (EFLN) has been recently investigated and applied
to nonlinear filtering. This brief proposes an adaptive EFLN filtering algorithm based on a …