The study focuses on the fault signals of rolling bearings, which are characterized by nonlinearity, periodic impact, and low signal-to-noise ratio. The advantages of entropy calculation in analyzing time series data were combined with the high calcu...
The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degr...
The vibration signals of rolling bearings are often nonlinear and non-stationary. Multiscale entropy (MSE) has been widely applied to measure the complexity of nonlinear mechanical vibration signals, however, at present only the single channel vibrat...
This paper analyses the complexity of multivariate electroencephalogram (EEG) signals in different frequency scales for the analysis and classification of focal and non-focal EEG signals. The proposed multivariate sub-band entropy measure has been bu...
Simultaneously analyzing multivariate time series provides an insight into underlying interaction mechanisms of cardiovascular system and has recently become an increasing focus of interest. In this study, we proposed a new multivariate entropy measu...
The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy entropy (FuzzyEn), introduced to measure the complexity...
So far, most articles using the multivariate multi-scale entropy algorithm mainly use algorithms to analyze the multivariable signal complexity without clearly describing what characteristics of signals these algorithms measure and what factors affec...
This study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer’s disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a...
In medicine, artificial neural networks (ANN) have been extensively applied in many fields to model the nonlinear relationship of multivariate data. Due to the difficulty of selecting input variables, attribute reduction techniques were widely used t...
Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience. Multivariate multiscale sample entropy (MSE–mvMSE) is a popular no...
The meta-synthesis method has achieved good results in China’s aerospace engineering and population economic regulation. This theoretical achievement obtained from engineering practice becomes an effective way to solve complex decision-making p...
Precipitation deficit can affect different natural resources such as water, soil, rivers and plants, and cause meteorological, hydrological and agricultural droughts. Multivariate drought indexes can theoretically show the severity and weakness of va...
The spatial fragmentation of high-resolution remote sensing images makes the segmentation algorithm put forward a strong demand for noise immunity. However, the stronger the noise immunity, the more serious the loss of detailed information, which eas...
Estimation of soil moisture distribution in desert regions is challenged by the deep unsaturated zone and the extreme natural environment. In this study, an entropy-based method, consisting of information entropy, principle of maximum entropy (PME),...
In the context of global climate change, the ecological environment of Tibet has been gaining attention given its unique geographical and fragile nature. In this study, to understand the pollution status of the surface water of Tibet, China, we colle...
Wind farm (WF) equivalence is an effective method to achieve accurate and efficient simulation of large-scale WF. Existing equivalent models are generally suitable for one certain or very few scenarios, and have difficulty reflecting the multiple asp...
Regional extreme rainfall events have occurred frequently in China, and subway tunnel construction faces possible threats under extreme weather conditions. Thus, in this study, we used the set pair analysis (SPA) approach to the construction safety e...
Background: Heart rate variability (HRV) is affected by many factors. This paper aims to explore the impact of water temperature (WT) on HRV during bathing. Methods: The bathtub WT was preset at three conditions: i.e., low WT (36–38 °C), medium WT (3...
Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattered studies have investigated brain electrophysiological disconnectivity of patients with generalized...
Fault diagnostic techniques can reduce the requirements for the experience of maintenance crews, accelerate maintenance speed, reduce maintenance cost, and increase electric energy production profitability. In this paper, a new hybrid fault diagnosis...
Precise forecasting of reference evapotranspiration (ET0) is one of the critical initial steps in determining crop water requirements, which contributes to the reliable management and long-term planning of the world’s scarce water sources. This...