In an electroencephalogram-(EEG-) based brain–computer interface (BCI), a subject can
directly communicate with an electronic device using his EEG signals in a safe and …

Electroencephalogram (EEG) signals are generated from central nervous system which are
difficult to disguise, leading to its popularity in emotion recognition. Recently, semi …

This paper explores the boosting ridge (BR) framework in the extreme learning machine
(ELM) community and presents a novel model that trains the base learners as a global …

Brain-computer interface (BCI) is a viable alternative communication strategy for patients of
neurological disorders as it facilitates the translation of human intent into device commands …

In this article, we propose a novelteacher–student-based label propagation deep
semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 …

Extreme learning machine (ELM) has received considerable attention due to its rapid
learning speed and powerful fitting capabilities. One of its important variants, the elastic-net …

Objective Time-consuming data labeling in brain-computer interfaces (BCIs) raises many
problems such as mental fatigue and is one key factor that hinders the real-world adoption of …

The conventional semisupervised extreme learning machine (SS-ELM) algorithm can
provide a solution to the lack of labeled samples in wind turbine blade icing fault detection …

A novel semi-supervised learning method is proposed to better utilize labeled and
unlabeled samples to improve classification performance. However, there is exists the …

As a single‐layer feedforward network (SLFN), extreme learning machine (ELM) has been
successfully applied for classification and regression in machine learning due to its faster …