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Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals

机译：基于1D八进制模式，小波变换和EEG信号的癫痫攻击识别

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Türker Tuncer; Sengul Dogan; Ganesh R. Naik; Paweł Pławiak;
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年度 2021
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1. Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals [J] . Tuncer Turker, Dogan Sengul, Naik Ganesh R., Multimedia Tools and Applications . 2021,第16期

机译：基于1D八进制模式，小波变换和脑电图信号的癫痫攻击识别
2. CLASSIFICATION OF EEG SIGNALS FOR DETECTION OF EPILEPTIC SEIZURES BASED ON WAVELETS AND STATISTICAL PATTERN RECOGNITION [J] . Dragoljub Gajic, Zeljko Djurovic, Stefano Di Gennaro, Biomedical Engineering: Applications, Basis and Communications . 2014,第2期

机译：基于小波和统计模式识别的癫痫发作脑电信号分类
3. EEG signal processing for epilepsy seizure detection using 5-level Db4 discrete wavelet transform, GA-based feature selection and ANN/SVM classifiers [J] . Omidvar Mehdi, Zahedi Abdulhamid, Bakhshi Hamidreza Journal of ambient intelligence and humanized computing . 2021,第11期

机译：EEG信号处理用于癫痫癫痫发作检测的使用5级DB4离散小波变换，基于GA的特征选择和ANN / SVM分类器
4. Epilepsy Seizure Detection in EEG Signals Using Wavelet Transforms and Neural Networks [C] . E. Juarez-Guerra, V. Alarcon-Aquino, P. Gomez-Gil International Joint Conference on Computer, Information, and Systems Sciences, and Engineering . 2015

机译：小波变换和神经网络在脑电信号中癫痫发作的检测
5. Real-time vision-based lane detection with 1D Haar Wavelet transform on Raspberry Pi. [D] . Sudini, Vikas Reddy. 2017

机译：在Raspberry Pi上使用一维Haar小波变换进行基于视觉的实时车道检测。
6. Classification of Motor Functions from Electroencephalogram (EEG) Signals Based on an Integrated Method Comprised of Common Spatial Pattern and Wavelet Transform Framework [O] . Norashikin Yahya, Huwaida Musa, Zhong Yi Ong, 2019

机译：基于公共空间模式和小波变换框架的集成方法从脑电图（EEG）信号对运动功能进行分类
7. Classification of EEG Signals for Detection of Epileptic Seizures Based on Wavelets and Statistical Pattern Recognition [O] . D. Gajic, Z. Djurovic, S. Di Gennaro, 2015

机译：基于小波和统计模式识别的癫痫发作检测脑电信号分类

Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals

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