Fast Fourier Transform and Ensemble Model to Classify Epileptic EEG Signals-Reference-Cited by-同舟云学术

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Fast Fourier Transform and Ensemble Model to Classify Epileptic EEG Signals

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
language:
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Author:

Lafta Raid¹,Alshaheen Hisham²,Wang Biao³,Tao Xiaohui⁴,Li Lingling⁵,Zhang Kexin⁵,Zhang Ji⁴

Affiliation:

1. University of Thi-Qar,Dep. of Studies & Planning,Iraq

2. University of Thi-Qar,College of Engineering,Iraq

3. Zhejiang Lab,China

4. University of Southern Queensland,Australia

5. Zhengzhou University of Aeronautics,School of Intelligent Engineering,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10020818.pdf?arnumber=10020818

Reference8 articles.

1. An Attention-Based Wavelet Convolution Neural Network for Epilepsy EEG Classification

2. Autonomous deep feature extraction based method for epileptic EEG brain seizure classification

3. High-Performance Seizure Detection System Using a Wavelet-Approximate Entropy-fSVM Cascade With Clinical Validation

4. Automatic Epileptic Seizure Detection in EEG Using Nonsubsampled Wavelet–Fourier Features

5. Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm

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