Epilepsy disorder detection and diagnosis using empirical mode decomposition and deep learning architecture-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Epilepsy disorder detection and diagnosis using empirical mode decomposition and deep learning architecture

Published:2022-02-28 Issue:11 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Srinath Rajagopalan¹^ORCID,Gayathri Rajagopal²^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

2. Department of Electronics and Communication Engineering Sri Venkateswara College of Engineering Sriperumbudur India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6903

Reference27 articles.

1. Classification of focal and non-focal EEG signals using neighborhood component analysis and machine learning algorithms

2. A novel approach for automated detection of focal EEG signals using empirical wavelet transform

3. Multifractal detrended fluctuation analysis based novel feature extraction technique for automated detection of focal and non‐focal electroencephalogram signals

4. Automated focal EEG signal detection based on third order cumulant function

5. An automatic detection of focal EEG signals using new class of time–frequency localized orthogonal wavelet filter banks

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automatic focal EEG identification based on deep reinforcement learning;Biomedical Signal Processing and Control;2023-05

2. Comparing Machine Learning and Deep Learning Approaches to Diagnose Epilepsy Disease;Lecture Notes in Electrical Engineering;2023

3. Epileptic Seizure Detection Using a Hybrid 1D CNN-Machine Learning Approach from EEG Data;Journal of Healthcare Engineering;2022-11-29

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3