An Innovative Information-Based Strategy for Epileptic EEG Classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
https://link.springer.com/content/pdf/10.1007/s11063-023-11253-w.pdf
Reference58 articles.
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2. Prasad DK, Liu S, Chen SHA, Quek C (2018) Sentiment analysis using EEG activities for suicidology. Expert Syst Appl 103:206–217. https://doi.org/10.1016/j.eswa.2018.03.011
3. Mahapatra AG, Horio K (2018) Classification of ictal and interictal EEG using RMS frequency, dominant frequency, root mean instantaneous frequency square and their parameters ratio. Biomed Signal Process Control 44:168–180. https://doi.org/10.1016/j.bspc.2018.04.007
4. Scally B, Burke MR, Bunce D, Delvenne JF (2018) Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging. Neurobiol Aging 71:149–155. https://doi.org/10.1016/j.neurobiolaging.2018.07.004
5. Sanila S, and Sathyalakshmi S (2021) Big data and machine learning analytics to detect epileptic seizures with minimum delay using random window optimization. In: V. Bhateja, S.L. Peng, S.C. Satapathy, Y.D. Zhang (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore, 2021. https://doi.org/10.1007/978-981-15-5788-0_22
Cited by 2 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. EpilConNet: A Novel Multi-Class Epileptic Seizure Classification Model;Inteligencia Artificial;2024-07-31
2. E-MFNN: an emotion-multimodal fusion neural network framework for emotion recognition;PeerJ Computer Science;2024-04-19
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