Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Epilepsy recognition based on electroencephalogram (EEG) and artificial intelligence
technology is the main tool of health analysis and diagnosis in Internet of medical things …

The epileptic seizure detection and classification is of great significance for clinical
diagnosis and treatment. To realize the detection and classification of epileptic seizure, this …

This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and
a conventional classifier for epileptic seizure detection. The signal segments of a channel of …

The detection and identification of epileptic seizures attracted considerable relevance for the
neurophysiologists. In order to accomplish the detection of epileptic seizures or equivalently …

Electroencephalographic signals (EEG signals) processing has become very popular
nowadays due to its effectiveness in dealing with and treating various disorders associated …

Electroencephalogram (EEG), also referred to as brain wave (BW), is a physiological
phenomenon that depicts how the human brain functions. Brain wave analysis is …

Ramanujan Fourier transform is one of the efficient multiresolution analysis tools, but it only
works for stationary or periodically characterized signals. Affine Fourier transform, a general …

Many approaches to automated epileptic seizure detection share a common challenge—the
trade-off between recall and precision. This study aims to develop a novel approach for …

在多源耦合强噪声干扰下, 滚动轴承的早期故障特征信号往往很难进行快速而又准确地提取.
针对现有研究中存在的抗噪能力较弱, 计算效率较低等问题, 一种基于仿真驱动的Ramanujan …