Improved sparse low-rank model via periodic overlapping group shrinkage and truncated nuclear norm for rolling bearing fault diagnosis
Q Zhang, X Li, H Mao, Z Huang, Y Xiao… - Measurement …, 2023 - iopscience.iop.org
The early faults of rolling bearings are the common causes of rotating machinery failures.
Rolling bearings with local faults usually generate periodic shocks during operation, but the …
Rolling bearings with local faults usually generate periodic shocks during operation, but the …
Machine learning based electrocardiogram peaks analyzer for Wolff-Parkinson-White syndrome
MA Merbouti, D Cherifi - Biomedical Signal Processing and Control, 2023 - Elsevier
The slurred upstroke named Delta in an Electrocardiogram (ECG) signal is known as the
main indicator of the existence of the Wolff-Parkinson-White (WPW) pattern. Previous studies …
main indicator of the existence of the Wolff-Parkinson-White (WPW) pattern. Previous studies …
Elicitation of fetal ECG from abdominal recordings using Blind Source Separation techniques and Robust Set Membership Affine Projection algorithm for signal quality …
Background: The utilization of non-invasive techniques for fetal cardiac health surveillance
is pivotal in evaluating fetal well-being throughout the gestational period. This process …
is pivotal in evaluating fetal well-being throughout the gestational period. This process …
Aircraft engine remaining useful life prediction: A comparison study of Kernel Adaptive Filtering architectures
GD Karatzinis, YS Boutalis… - Mechanical Systems and …, 2024 - Elsevier
Abstract Predicting the Remaining Useful Life (RUL) of mechanical systems poses
significant challenges in Prognostics and Health Management (PHM), impacting safety and …
significant challenges in Prognostics and Health Management (PHM), impacting safety and …
Identification and classification of epileptic EEG signals using invertible constant-Q transform-based deep convolutional neural network
AS Eltrass, MB Tayel, AF El-Qady - Journal of Neural Engineering, 2022 - iopscience.iop.org
Context. Epilepsy is the most widespread disorder of the nervous system, affecting humans
of all ages and races. The most common diagnostic test in epilepsy is the …
of all ages and races. The most common diagnostic test in epilepsy is the …
A robust ECG signal enhancement technique through optimally designed adaptive filters
Electrocardiogram (ECG) signals are widely used in medical diagnostics to analyze the
electrical activity of the heart. However, in clinical practice, these signals are often …
electrical activity of the heart. However, in clinical practice, these signals are often …
Cardiac arrhythmias detection framework based on higher-order spectral distribution with deep learning
S Karthikeyani, S Sasipriya, M Ramkumar - Biomedical Signal Processing …, 2024 - Elsevier
In this article, a new framework for arrhythmia identification using higher-order spectral
distributions and deep learning approaches has been proposed. The input signal is first pre …
distributions and deep learning approaches has been proposed. The input signal is first pre …
Discriminative Subspace Learning With Adaptive Graph Regularization
Many subspace learning methods based on low-rank representation employ the nearest
neighborhood graph to preserve the local structure. However, in these methods, the nearest …
neighborhood graph to preserve the local structure. However, in these methods, the nearest …
基于改进ICEEMDAN 的肌电干扰去除算法.
李国权, 朱双青, 黄正文, 庞宇 - Journal of Chongqing …, 2023 - search.ebscohost.com
肌电干扰使心电信号产生细小波纹ꎬ 频率分布范围宽广ꎬ 严重影响心电图的准确性ꎬ
不利于病情诊断ꎮ 针对心电信号中肌电干扰去除效果不好的问题ꎬ 提出基于改进的自适应噪声 …
不利于病情诊断ꎮ 针对心电信号中肌电干扰去除效果不好的问题ꎬ 提出基于改进的自适应噪声 …
Two Stage Step-Size Adaptive Filter Design for ECG Denoising
An adaptive filter is a system that includes a linear filter with a converter controlled by input
variables and the ability to change those parameters using an optimization technique. In the …
variables and the ability to change those parameters using an optimization technique. In the …