[1] LI Zhiping.Multi-channel seizure prediction based on support vector machine[J].Computer Engineering,2014,40(2):199-202,207.(in Chinese) 李志萍.基于支持向量机的多通道癫痫发作预测[J].计算机工程,2014,40(2):199-202,207. [2] ZHANG Tao,CHEN Wanzhong,LI Mingyang.Automatic seizure detection of electroencephalogram signals based on frequency slice wavelet transform and SVM[J].Acta Physica Sinica,2016,65(3):635-642.(in Chinese) 张涛,陈万忠,李明阳.基于频率切片小波变换和支持向量机的癫痫脑电信号自动检测[J].物理学报,2016,65(3):635-642. [3] NIU Baodong,MA Jinwen.Automatic detection of epileptic seizure through Hilbert-Huang transform[J].Journal of Signal Processing,2016,32(7):764-770.(in Chinese) 牛宝东,马尽文.基于希尔伯特黄变换的癫痫自动检测[J].信号处理,2016,32(7):764-770. [4] ALTUNAY S,TELATAR Z,EROGUL O.Epileptic EEG detection using the linear prediction error energy[J].Expert Systems with Applications,2010,37(8):5661-5665. [5] JOSHI V,PACHORI R B,VIJESH A.Classification of ictal and seizure-free EEG signals using fractional linear prediction[J].Biomedical Signal Processing and Control,2014,9(1):1-5. [6] DENG Zhaohong,CHEN Junyong,LIU Jiefang,et al.Radial basis minimax probability classification tree for epilepsy electroencephalogram signal recognition[J].Journal of Electronics and Information Technology,2016,38(11):2848-2855.(in Chinese) 邓赵红,陈俊勇,刘解放,等.面向癫痫脑电图信号识别的径向基最小最大概率分类树[J].电子与信息学报,2016,38(11):2848-2855. [7] LIU Long,LI Sheng,WANG Yiqing.EEG signal denoising and feature extraction based on wavelet packet transform[J].Computer Engineering and Science,2015,37(4):790-795.(in Chinese) 刘珑,李胜,王轶卿.基于小波包变换的脑电波信号降噪及特征提取[J].计算机工程与科学,2015,37(4):790-795. [8] HE Wangpeng,YANG Lin,WANG Fang,et al.Identification of epileptic EEG signals based on the tunable q-factor wavelet transform[J].Journal of Biomedical Engineering Research,2017(4):346-350.(in Chinese) 贺王鹏,杨琳,王芳,等.基于TQWT的癫痫脑电信号的识别[J].生物医学工程研究,2017(4):346-350. [9] CHEN Lanlan,ZHANG Jian,ZOU Junzhong,et al.A framework on wavelet-based nonlinear features and extreme learning machine for epileptic seizure detection[J].Biomedical Signal Processing and Control,2014,10(1):1-10. [10] LI Dongmei,ZHANG Yang,YANG Ridong,et al.Classification and prediction of EEG based on empirical mode decomposition[J].Journal of Biomedical Engineering Research,2017,36(1):33-37.(in Chinese) 李冬梅,张洋,杨日东,等.经验模式分解与代价敏感支持向量机在癫痫脑电信号分类中的应用[J].生物医学工程研究,2017,36(1):33-37. [11] PACHORI R B,BAJAJ V.Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition[J].Computer Methods and Programs in Biomedicine,2011,104(3):373-381. [12] POLAT K,GÜNE S.Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform[J].Applied Mathematics and Computation,2007,187(2):1017-1026. [13] FU Kai,QU Jianfeng,CHAI Yi,et al.Classification of seizure based on the time-frequency image of EEG signals using HHT and SVM[J].Biomedical Signal Processing and Control,2014,13(5):15-22. [14] CHATLANI N,SORAGHANJ J.Local binary patterns for 1-D signal processing[C]//Proceedings of Signal Processing Conference.Washington D.C.,USA:IEEE Press,2010:95-99. [15] TAO Huawei,LIU Jingjing,LIANG Ruiyu,et al.Gabor block spectrum features based on local binary pattern for speech emotion recognition[J].Journal of Signal Processing,2016,32(5):505-511.(in Chinese) 陶华伟,柳晶晶,梁瑞宇,等.面向语音情感识别的Gabor分块局部二值模式特征[J].信号处理,2016,32(5):505-511. [16] KUMAR T S,KANHANGAD V,PACHORIR B.Classification of seizure and seizure-free EEG signals using local binary patterns[J].Biomedical Signal Processing and Control,2015,15:33-40. [17] ANDRZEJAK R G,LEHNERTZ K,MORMANN F,et al.Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity:dependence on recording region and brain state[J].Physical Review E,2001,64(6):1907-1915. [18] KAYA Y,UYAR M,TEKIN R,et al.1D-local binary pattern based feature extraction for classification of epileptic EEG signals[J].Applied Mathematics and Computation,2014,243:209-219. [19] PEKER M,SEN B,DELEN D.A novel method for automated diagnosis of epilepsy using complex-valued classifiers[J].IEEE Journal of Biomedical and Health Informatics,2015,20(1):108-118. [20] TAWFIK N S,YOUSSEF S M,KHOLIEF M.A hybrid automated detection of epileptic seizures in EEG records[J].Computers and Electrical Engineering,2016,53:177-190. [21] ISIK H,SEZER E.Diagnosis of epilepsy from electro-encephalography signals using multilayer perceptron and Elman artificial neural networks and wavelet transform[J].Journal of Medical Systems,2012,36(1):1-13. [22] JAISWAL A K.Local pattern transformation based feature extraction techniques for classification of epileptic EEG signals [J].Biomedical Signal Processing and Control,2017,34:81-92. [23] NICOLAOU N,GEORGIOU J.Detection of epileptic electroencephalogram based on permutation entropy and support vector machines[J].Expert Systems with Applications,2012,39(1):202-209. [24] KUMAR Y,DEWAL M L,ANANDR S.Epileptic seizure detection using DWT based fuzzy approximate entropy and support vector machine[J].Neurocomputing,2014,133(8):271-279. |