benchmark testing; biomechanics; electroencephalography; entropy; medical signal processing; signal classification; statistical analysis; wavelet transforms; ANOVA analysis; EEG signals; K-nearest neighbor-based classifiers; dual tree complex wavelet transform domain; electroencephalogram signals; imaginary coefficients; motor imagery left hand movements; motor imagery movements detection; motor imagery right hand movements; norm entropy; publicly available benchmark BCI-competition 2003 Graz motor imagery dataset; standard deviation; statistical features; Accuracy; Analysis of variance; Electroencephalography; Histograms; Standards; Support vector machines; Timing; Dual Tree Complex Wavelet Transform (DTCWT); Electroencephalogram (EEG); Entropy; KNN classifier; Standard deviation;
机译:使用双树复数小波变换域中的自动选择特征从脑电信号中识别运动图像运动
机译:基于双树复小波变换和自适应模型选择的燕子脑电信号运动图像检测
机译:双树复小波变换和最小二乘支持向量机在癫痫发作检测系统中对脑电信号的分类
机译:电机图像在双树复杂小波变换域中使用统计功能检测EEG信号
机译:双树复小波变换在突发检测和射频指纹分类中的应用
机译:基于双树复小波变换和机器学习算法的脑电图癫痫发作检测与分类
机译:基于双树复杂小波变换和机器学习算法的EEG癫痫癫痫发作检测和分类