The brain–computer interface (BCI) is an emerging technology that has the potential to
revolutionize the world, with numerous applications ranging from healthcare to human …

Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …

Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …

Objective. Electroencephalography (EEG) analysis has been an important tool in
neuroscience with applications in neuroscience, neural engineering (eg Brain–computer …

Over the last few decades, electroencephalogram (EEG) has become one of the most vital
tools used by physicians to diagnose several neurological disorders of the human brain and …

In the context of motor imagery, electroencephalography (EEG) data vary from subject to
subject such that the performance of a classifier trained on data of multiple subjects from a …

In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …

Optimal feature extraction for multi-category motor imagery brain-computer interfaces (MI-
BCIs) is a research hotspot. The common spatial pattern (CSP) algorithm is one of the most …

Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …

The feedforward neural network based on randomization has been of great interest in the
scientific community, particularly extreme learning machines, due to its simplicity, training …