In recent years, there has been major interest in the exposure to physical therapy during
rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and …

Compressive sensing generally relies on the ℓ 2 norm for data fidelity, whereas in many
applications, robust estimators are needed. Among the scenarios in which robust …

This paper addresses the issue of robust sparse recovery in compressive sensing (CS) in
the presence of impulsive measurement noise. Recently, robust data-fitting models, such as …

A new long-range-dependent (LRD) degradation model is described based on the
generalized Cauchy (GC) process. The GC process is a two-parameter model, which …

The degradation process of lithium-ion batteries has memory, ie it has long-range
dependence (LRD). In this paper, an iterative model of the generalized Cauchy (GC) …

The local irregularity and global correlation of wind speed can be described by the fractal
dimension D and the Hurst parameter H. However, the existing mathematical models imply a …

Commonly employed reconstruction algorithms in compressed sensing (CS) use the L2
norm as the metric for the residual error. However, it is well-known that least squares (LS) …

Non-stationary physiological noise poses significant difficulties due to its time-varying and
previously unknown characteristics. When processing electronystagmographic signals …

Advances in sensor technology have enabled the collection of large-scale datasets. Such
datasets can be extremely noisy and often contain a significant amount of outliers that result …

Abstract While Deep Neural Networks (DNNs) have shown incredible performance in a
variety of data, they are brittle and opaque: easily fooled by the presence of noise, and …