electroencephalography; medical signal processing; neurophysiology; time series; waveform analysis; EC state; EEG physiological states; EEG time series; EEG waveform; EO state; PE development; PE limitations; VOT state; WPE ability; WPE potential; brain physiological states; electroencephalographic time series; electroencephalographic waveform; electroencephalography time series; eye-closed EEG state; eye-open EEG state; large artifact marker; linear discrimination analysis; low frequency artifact; modified PE version; motif pattern differentiation; noise sensitivity; pemutation entropy; physiological state analysis; physiological state identification; relative motif ocurrence; time series ranking value-based motifs; visual oddball task; weighted-permutation entropy; Accuracy; Complexity theory; Electroencephalography; Entropy; Physiology; Time series analysis; Visualization; CPEI; EEG; PE; Weighted Permutation Entropy; eye-blink;
机译:加权置换熵:包含幅度信息的时间序列的复杂性度量
机译:精制复合多尺度加权 - 金融时序系列熵熵
机译:使用广义样本熵和替代数据分析评估时间序列中的生理复杂性
机译:加权置换熵作为不同生理状态的脑电图时间序列的复杂性度量
机译:一系列连续的家庭治疗课程中的熵和复杂性:寻求家庭动力学的经验非线性指标。
机译:利用传感器网络的灵活多尺度熵测量时间序列的复杂性和可预测性
机译:修正刘,X。;江,a。;徐,N。薛,J。增量熵作为时间序列复杂性的度量。 Entropy 2016,18,22