Pattern analysis often requires a pre-processing stage for extracting or selecting features in
order to help the classification, prediction, or clustering stage discriminate or represent the …

This tutorial explains Linear Discriminant Analysis (LDA) and Quadratic Discriminant
Analysis (QDA) as two fundamental classification methods in statistical and probabilistic …

There is a wide area of application that uses cerebral activity to restore capabilities for
people with severe motor disabilities, and actually the number of such systems keeps …

A brain–machine interface (BMI) based on motor imagery (MI) enables the control of devices
using brain signals while the subject imagines performing a movement. It plays a key role in …

Background Brain–computer interface (BCI) is a communication pathway applied for
pathological analysis or functional substitution. BCI based on functional substitution enables …

Brain-computer interfaces (BCIs) is promising in interacting with machines through
electroencephalogram (EEG) signal. The compact end-to-end neural network model for …

This paper comprehensively reviews hardware acceleration techniques and the deployment
of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals …

Speech recognition and in other word communication between computers and human as a
sub field of computational linguistics or Natural Language Processing (NLP) has a long …

Deep learning (DL) has been widely employed in brain--machine interfaces (BMIs) to
decode subjects' intentions based on recorded brain activities enabling direct interaction …

In the research of motor imagery brain‐computer interface (MI‐BCI), traditional
electroencephalogram (EEG) signal recognition algorithms appear to be inefficient in …