Denoising of Ictal EEG Data Using Semi-Blind Source Separation Methods Based on Time-Frequency Priors-Reference-Cited by-同舟云学术

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Denoising of Ictal EEG Data Using Semi-Blind Source Separation Methods Based on Time-Frequency Priors

Published:2015-05 Issue:3 Volume:19 Page:839-847
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Hajipour Sardouie Sepideh,Shamsollahi Mohammad Bagher,Albera Laurent,Merlet Isabelle

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/6221020/7104199/06866858.pdf?arnumber=6866858

Cited by 13 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. EEG emotion recognition using EEG-SWTNS neural network through EEG spectral image;Information Sciences;2024-10

2. Higher-Order Semi-Blind Source Separation Approaches Using Canonical Polyadic (CP) Decomposition;2023 31st International Conference on Electrical Engineering (ICEE);2023-05-09

3. EOG Eye Blink Artifact Removal using Multivariate Variational Mode Decomposition and PCA;2022 IEEE 6th Conference on Information and Communication Technology (CICT);2022-11-18

4. Auto-Denoising for EEG Signals Using Generative Adversarial Network;Sensors;2022-02-23

5. A Unified Approach for Simultaneous Graph Learning and Blind Separation of Graph Signal Sources;IEEE Transactions on Signal and Information Processing over Networks;2022

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