The present study proposes the Robust DLMS (RDLMS) algorithm for a robust estimation
over adaptive networks. Instead of minimizing the mean square error (MSE), the RDLMS …

In this paper, a novel adaptive time delay estimation (TDE) method under the existence of
amplitude attenuation is proposed for the impulsive noise environment. We present a closed …

In this brief, a robust correntropy-based adaptive learning algorithm, called the adaptive
kernel recursive maximum correntropy criterion, is proposed by considering an adaptive …

A robust cyclic array beamforming method is proposed for cyclostationary signals to counter
against the cycle frequency error (CFE) in Gaussian and impulsive noise environments. In …

This paper addresses the problem of multiple‐hypothesis detection. In many applications,
assuming the Gaussian distribution for undesirable disturbances does not yield a sufficient …

Impulsive noises are widely existing in various systems like noise cancellation system and
wireless communication systems, where adaptive filtering (AF) is always employed to …

Correntropy as an efficient information theoretic (ITL) criterion has been extensively applied
in many non-Gaussian applications. In order to maximize correntropy, several optimization …

Distributed multitask learning over adaptive networks with non‐ideal links is studied in this
paper. The performance of an adaptive multitask network with wireless communication links …

The past decade has seen a rapid application of information theoretic learning (ITL) criteria
in robust signal processing and machine learning problems. Generally, in ITL's literature, it is …

Signal processing is crucial that as one sends information, there is a corresponding process
to encode, decode, and clean the signal of unwanted noise and disruptions via use of filters …