A novel deep learning approach with data augmentation to classify motor imagery signals
Z Zhang, F Duan, J Sole-Casals… - IEEE …, 2019 - ieeexplore.ieee.org
Brain-computer interface provides a new communication bridge between the human mind
and devices, depending largely on the accurate classification and identification of non …
and devices, depending largely on the accurate classification and identification of non …
Application of entropy measures on intrinsic mode functions for the automated identification of focal electroencephalogram signals
The brain is a complex structure made up of interconnected neurons, and its electrical
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
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 …
addressing the increasing demand for electricity in the modern era to overcome future …
Global research on artificial intelligence-enhanced human electroencephalogram analysis
The application of artificial intelligence (AI) technologies in assisting human
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
EEG-based emotion analysis using non-linear features and ensemble learning approaches
Recognition of emotions based on electroencephalography (EEG) has become one of the
most emerging topics for healthcare, education system, knowledge sharing, gaming, and …
most emerging topics for healthcare, education system, knowledge sharing, gaming, and …
Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with …
New and improved drought models based on the World Meteorological Organization
approved Standardized Precipitation Index, principally at multiple timescale horizons, are …
approved Standardized Precipitation Index, principally at multiple timescale horizons, are …
Review of EEG Affective Recognition with a Neuroscience Perspective
Emotions are a series of subconscious, fleeting, and sometimes elusive manifestations of
the human innate system. They play crucial roles in everyday life—influencing the way we …
the human innate system. They play crucial roles in everyday life—influencing the way we …
Mean-optimized mode decomposition: An improved EMD approach for non-stationary signal processing
J Zheng, H Pan - ISA transactions, 2020 - Elsevier
As an effective signal separation method of non-stationary signal, empirical mode
decomposition (EMD) has been widely used in the data or time series analysis of many …
decomposition (EMD) has been widely used in the data or time series analysis of many …
Deep learning methods for multi-channel EEG-based emotion recognition
Currently, Fourier-based, wavelet-based, and Hilbert-based time–frequency techniques
have generated considerable interest in classification studies for emotion recognition in …
have generated considerable interest in classification studies for emotion recognition in …
A newly developed integrative bio-inspired artificial intelligence model for wind speed prediction
Accurate wind speed (WS) modelling is crucial for optimal utilization of wind energy.
Numerical Weather Prediction (NWP) techniques, generally used for WS modelling are not …
Numerical Weather Prediction (NWP) techniques, generally used for WS modelling are not …