Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …

Rotating machines have been widely used in industrial engineering. The fault diagnosis of
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …

The vibration signal of the axle box bearing of the train is affected by the track excitation and
the random noise of the environment. The vibration signal is nonlinear and non-stationary …

Blind deconvolution has been proved to be an effective method for fault detection since it
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …

Slope entropy (SloEn) has been applied as a powerful nonlinear dynamic tool for signal
complexity measurement and is widely used for ship-radiated noise signal (S-RNS) feature …

To extract more distinguishing features of ships, slope entropy (SloE) is introduced into
underwater acoustic signal processing as a new feature to analyze ship-radiated noise …

Recently, coded permutation entropy has been proposed, which enhances the noise
immunity by quadratic partitioning on the basis of permutation entropy. However, coded …

Lempel-Ziv complexity (LZC) is one of the most important metrics for detecting dynamic
changes in non-linear signals, but due to its dependence on binary conversion, LZC tends to …

Alzheimer's disease (AD) is the most common neurodegenerative disease among the
elderly with a progressive decline in cognitive function significantly affecting quality of life …

To fully mine the effective fault information and improve the fault diagnosis accuracy, a novel
fault diagnosis approach for rolling bearings is proposed by integrating variational mode …