This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …

In the era of the “Industry 4.0” revolution, self-adjusting and unmanned machining systems
have gained considerable interest in high-value manufacturing industries to cope with the …

In order to improve the diagnosis accuracy and solve the weak fault signal of rolling element
of rolling bearings due to long transmission path, a novel fault diagnosis method based on …

Accurate prediction of floating offshore platform motion (FOPM) is very important to control
the movement of the platform and the normal operation of the equipment on the platform …

Signal decomposition is an effective tool to assist identification of modal information in time-
domain signals. Two signal decomposition methods, including the empirical wavelet …

During sleep, cortical and subcortical structures within the brain engage in highly structured
oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to …

It is generally accepted that the activities of the autonomic nervous system (ANS), which
consists of the sympathetic (SNS) and parasympathetic nervous systems (PNS), are …

The bearing vibration signal with strong non-stationary properties is normally composed of
multiple components (eg periodic impulses, background noise and other external signal) …

Solar energy is an alternative renewable energy resource that has the potential of cleanly
addressing the increasing demand for electricity in the modern era to overcome future …

Rolling bearings are widely used in rotary machinery systems. The measured vibration
signal of any part linked to rolling bearings contains fault information when failure occurs …