Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most
common cause of Dementia. Neuroimaging analyses, such as T1 weighted magnetic …

This work investigated the use of an ensemble deep random vector functional link (edRVFL)
network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low …

Randomized shallow/deep neural networks with closed form solution avoid the
shortcomings that exist in the back propagation (BP) based trained neural networks …

Alzheimer's disease is incurable at the moment. If it can be appropriately diagnosed, the
correct treatment can postpone the patient's illness. To aid in the diagnosis of Alzheimer's …

Conventional functional connectivity network (FCN) based on resting-state fMRI (rs-fMRI)
can only reflect the relationship between pairwise brain regions. Thus, the hyper …

The kernel fuzzy clustering algorithms can explore the non-linear relations of pixels in an
image. However, most of kernel-based methods are computationally expensive for color …

Randomized neural networks (RNNs) have shown outstanding performance in many
different fields. The superiority of having fewer training parameters and closed-form …

The random vector functional link (RVFL) network is a prominent classification model with
strong generalization ability. However, RVFL treats all samples uniformly, ignoring whether …

The domain of machine learning is confronted with a crucial research area known as class
imbalance (CI) learning, which presents considerable hurdles in the precise classification of …