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 …

Objective. Fluorescence molecular tomography (FMT) is a promising non-invasive optical
molecular imaging technology with strong specificity and sensitivity that has great potential …

We present HandAvatar, a novel representation for hand animation and rendering, which
can generate smoothly compositional geometry and self-occlusion-aware texture …

In the past decade, sparse and low-rank recovery has drawn much attention in many areas
such as signal/image processing, statistics, bioinformatics, and machine learning. To …

Anomaly detection has attracted much attention in recent years since it plays a crucial role in
many domains. Various anomaly detection approaches have been proposed, among which …

Imbalanced data cause deep neural networks to output biased results, and it becomes more
serious when facing extremely imbalanced data regarding the outliers with tiny size (the …

A type of norm-adaption penalized least mean square/fourth (NA-LMS/F) algorithm is
proposed for sparse channel estimation applications. The proposed NA-LMS/F algorithm is …

As one of the recently proposed algorithms for sparse system identification, l_0 norm
constraint Least Mean Square (l_0-LMS) algorithm modifies the cost function of the …

The combination of the famed kernel trick and affine projection algorithms (APAs) yields
powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up …

In this paper, we propose a type of sparsity-aware set-membership normalized least mean
square (SM-NLMS) algorithm for sparse channel estimation and echo cancelation. The …