The electroencephalography (EEG) signal is a noninvasive and complex signal that has
numerous applications in biomedical fields, including sleep and the brain–computer …

Gunshot sounds are common in crimes, particularly those involving threats, harassment, or
killing. The gunshot sounds in crimes can create fear and panic among victims, often leading …

The Human Activity Recognition (HAR) system is the hottest research area in clinical
research. The HAR plays a vital role in learning about a patient's abnormal activities; based …

Epileptic seizure prediction using multi-channel electroencephalogram (EEG) signals is very
important in clinical therapy. A large number of channels lead to high computational …

In data analysis, when attempting to solve classification problems, we may encounter a large
number of features. However, not all features are relevant for the current classification, and …

With the expansion of vector-based classifiers to matrix-based classifiers, noise insensitivity
and sparsity have always been the focal points. Existing SMM and Pin-SMM enjoy the …

Purpose Twin support vector machine (TSVM) is an effective machine learning technique.
However, the TSVM model does not consider the influence of different data samples on the …

Abstract Twin Support Vector Machine (TSVM) transforms a single large quadratic
programming problem (QPP) in support vector machine (SVM) into two smaller QPPs by …

The growing demand for semi-autonomous human–machine systems has led to an
increased requirement for human fatigue detection. Direct and invasive approaches for …

Universum data sets, a collection of data sets that do not belong to any specific class in a
classification problem, give previous information about data in the mathematical problem …