Non-stationarity of EEG signals leads to high variability between subjects, making it
challenging to directly use data from other subjects (source domain) for the classifier in the …

Introduction Brain-computer interfaces (BCIs) are systems that acquire the brain's electrical
activity and provide control of external devices. Since electroencephalography (EEG) is the …

Multichannel electroencephalogram (EEG) signals, which directly reflects the brain's inner
workings state, is an powerful tool to diagnosis depression. For EEG-based depression …

The most common neurodegenerative disorder that slowly affects the functions of brain cells
affecting the memory, eventually resulting in loss of ability to perform even small things is …

Background and objective Steady-state visual evoked potential (SSVEP)-based brain-
computer interfaces (BCIs) aim to detect target frequencies corresponding to specific …

To address the high‐dimensional issues in credit risk assessment, an improved multilayer
restricted Boltzmann machine (RBM) based feature extraction method is proposed. In the …

Introduction Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary
and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult …

Steady-state visual evoked potentials (SSVEPs) are brain nonlinear responses evoked by
repetitive visual stimuli with specific frequencies. In addition to the frequency of visual …

Background: Accurately predicting the toxicity of ionic liquids is essential for promoting
sustainable chemical applications while mitigating environmental and health risks. The …

Depression, as a common yet severe mood disorder, can cause irreversible damage to the
brain if not detected and treated in a timely manner. Unfortunately, due to the current …