The steady-state visual evoked potential (SSVEP) detection technology is more suitable for
real-time brain-computer interface (BCI) systems due to its easy feature recognition, short …

Steady-state visual evoked potential (SSVEP) signal collected from the scalp typically
contains other types of electric signals, and it is important to remove these noise …

Introduction As an important human-computer interaction technology, steady-state visual
evoked potential (SSVEP) plays a key role in the application of brain computer interface …

This study proposed a data-driven NO x modelling framework that could capture the
multimodal operational characteristics of a utility boiler, improve the training sample quality …

This article focuses on proposing a new framework for self-organizing multichannel deep
learning system (SMDLS) to solve the problem of river turbidity monitoring, which is one of …

To accurately and effectively analyze electroencephalogram (EEG) with high complexity,
large amount of data, and strong uncertainty, brain–computer interface (BCI) cognitive …

Objective. Steady-state visual evoked potential (SSVEP) training feature recognition
algorithms utilize user training data to reduce the interference of spontaneous …

Brain computer interface (BCI) system based on steady-state visual evoked potentials
(SSVEP) has great potential for communication and control applications. The actual …

Objective Frequency recognition methods based on spatial filtering have been widely
studied to enhance the classification performance of steady-state visual evoked potential …

Steady-state visual evoked potential (SSVEP) is widely used in electroencephalogram
(EEG) control, medical detection, cognitive neuroscience, and other fields. However …