Structural damage identification has received considerable attention during the past
decades. Although several reviews have been presented, some new developments have …

Structural damages occur in modern structures during operations due to environmental and
human factors. The damages accumulating with time may lead to a significant decrease in …

Sparse modeling for signal processing and machine learning, in general, has been at the
focus of scientific research for over two decades. Among others, supervised sparsity-aware …

Acoustic data provide scientific and engineering insights in fields ranging from biology and
communications to ocean and Earth science. We survey the recent advances and …

This paper gives an overview of the majorization-minimization (MM) algorithmic framework,
which can provide guidance in deriving problem-driven algorithms with low computational …

Decoding brain activity from non-invasive electroencephalography (EEG) is crucial for brain-
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …

As intelligent sensing and sensor network systems have made progress and low‐cost online
structural health monitoring has become possible and widely implemented, large quantities …

Accurately forecasting crude oil prices has drawn much attention from researchers,
investors, producers, and consumers. However, the complexity of crude oil prices makes it a …

Most compressive sensing (CS) reconstruction methods can be divided into two categories,
ie model-based methods and classical deep network methods. By unfolding the iterative …

Nowadays, a large amount of information has to be transmitted or processed. This implies
high-power processing, large memory density, and increased energy consumption. In …