Multimedia Signal Process. Group, Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland;
autoregressive processes; brain-computer interfaces; electroencephalography; feature extraction; inference mechanisms; medical signal processing; signal classification; uncertainty handling; wavelet transforms; Dempster Shafer theory; EEG signal classification; autoregressive model; brain computer interface; distance-weighted KNN classifier; electroencephalogram; k-nearest neighbor classifier; wavelet decomposition; BCI; EEG; classification; nearest neighbor;
机译:基于Dempster-Shafer理论的k近邻分类规则
机译:基于Dempster-Shafer证据理论的振动和声学信号分类器融合,用于行星齿轮的故障诊断和分类
机译:基于EEG信号的K-intembors(K-NN)算法的k - 最近邻居分类算法的性能分析
机译:使用Dempster Shafer理论和K-incelte邻分类的EEG信号分类
机译:使用Dempster Shafer证据理论融合ECG / EEG以改善自动癫痫发作检测
机译:使用K近邻分类法从多通道EEG信号进行情感识别
机译:使用Dempster shafer理论和K-最近邻分类器对EEG信号进行分类