Brain-computer interface (BCI) speller is a system that provides an alternative
communication for the disable people. The brain wave is translated into machine command …

Electroencephalography (EEG) topographical representation (ETR) can monitor regional
brain activities and is emerging as a successful technique for causally exploring cortical …

In this paper, a novel multiscale convolutional neural network (MsCNN) architecture is
proposed for P300 based BCI speller. Major limitation of BCI system is that it requires a large …

Recently, the technique of nonlinear Lamb wave mixing has been developed for the
detection of fatigue crack in engineering structures. In this technique, two or three Lamb …

In this work, a brain–computer interface (BCI) system for character recognition has been
proposed based on the P300 signal. P300 signal classification is the most challenging task …

Spectral regression (SR), a graph-based learning regression model, can be used to extract
features from graphs to realize efficient dimensionality reduction. However, due to the SR …

Factorization-based analysis of multi-dimensional EEG (Electroencephalography) has
become increasingly important in neuroscience research and practices with the capability of …

Background Incorporating the time-frequency localization properties of Gabor transform
(GT), the complexity understandings of convolutional neural network (CNN), and histogram …

Objective. Brain–computer interface (BCI) systems decode electroencephalogram (EEG)
signals to establish a channel for direct interaction between the human brain and the …

Feature extraction plays an indispensable role in image and video technology. However, it is
difficult for traditional matrix based feature extraction methods to handle massive multi …