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 …

The failure of a rolling bearing may cause the shutdown of mechanical equipment and even
induce catastrophic accidents, resulting in tremendous economic losses and a severely …

How to measure the complexity of physiological signals in biological system is an open
problem. Various entropy algorithms have been presented, but most of them fail to account …

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 …

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 …

Intelligent fault diagnosis of rotating machinery is essentially a pattern recognition problem.
Meanwhile, effective feature extraction from the raw vibration signal is an important …

Slope entropy (SloEn) is an effective nonlinear dynamic method to represent the complexity
of time series, which has been extensively applied to various mechanical signal processing …

Slope entropy (SloEn) is an effective complexity analysis measure of signals that has been
applied to many areas in recent years. Whereas SloEn can only reflect the complexity …

Sleep stage classification is an important task for the timely diagnosis of sleep disorders and
sleep-related studies. In this paper, automatic scoring of sleep stages using …