The study of signals, processes, and systems has motivated the development of different
representations that can be used to analyze and understand them. Classical ways of …

Road surfaces suffer from sources of deterioration, such as weather conditions, constant
usage, loads, and the age of the infrastructure. These sources of decay generate anomalies …

Time series anomaly detection is a challenging problem due to the complex temporal
dependencies and the limited label data. Although some algorithms including both …

This comprehensive and engaging textbook introduces the basic principles and techniques
of signal processing, from the fundamental ideas of signals and systems theory to real-world …

Sleep related disorder causes diminished quality of lives in human beings. Sleep scoring or
sleep staging is the process of classifying various sleep stages which helps to detect the …

We investigate the impact of aliasing on generalization in Deep Convolutional Networks and
show that data augmentation schemes alone are unable to prevent it due to structural …

The development of information technology has had a significant impact on various areas of
human activity, including medicine. It has led to the emergence of the phenomenon of …

Traditional uncertainty quantification (UQ) algorithms are mostly developed for a fixed time
(term), such as hourly or daily predictions. Although a few UQ techniques can compute UQ …

We present a design of a new class of compactly supported antisymmetric biorthogonal
wavelet filter banks which have the analysis as well as the synthesis filters of even-length …

Abstract Design of time–frequency localized filters and functions is a classical subject in the
field of signal processing. Gabor's uncertainty principle states that a function cannot be …