As it was mentioned in the previous part of this work (Part I)—the advanced signal
processing methods are one of the quickest and the most dynamically developing scientific …

Brain-computer interfaces (BCIs) have emerged as a promising technology for enhancing
communication between the human brain and external devices. Electroencephalography …

As an important neurorecording technique, electroencephalography (EEG) is often
contaminated by various artifacts, which obstructs subsequent analysis. In recent years …

Cognitive/mental task classification using single/limited channel (s) electroencephalogram
(EEG) signals in real-time play an important role in designing portable brain-computer …

An objective distortion measure is very crucial to accurately quantify the distortion introduced
in the electroencephalogram (EEG) signal during the denoising process. Most of the existing …

Mental task categorization using single/limited channel (s) electroencephalogram (EEG)
signals is crucial for designing portable brain–computer interface and neurofeedback …

The classification of motor imagery (MI) task based on Electroencephalography (EEG) is an
important problem in brain-computer interface (BCI) system. The high-precision …

Electroencephalogram (EEG) is one of the common modalities of monitoring the mental
activities. Owing to the non-invasive availability of this system, its applicability has seen …

Electroencephalography (EEG) is an important noninvasive neural recording technique with
a broad application in the field of neurological instrumentation and measurement. However …

This paper presents a fractional one-dimensional convolutional neural network (CNN)
autoencoder for denoising the Electroencephalogram (EEG) signals which often get …