The wavelet entropy is defined for analyzing the complexity of the signals.
结合小波包熵分析脑电在不同大脑功能状态下的脑电复杂程度。
The contrast between wavelet transform maximal modulus and wavelet entropy shows that the latter is a better approach to detect transient signal accurately and timely.
利用小波变换模极大值和小波熵测度分别对其进行检测，对比表明，小波熵测度能更准确、实时地检测到各种暂态信号。
Wavelet entropy analysis shows that after sleep deprivation, compared with natural sleep, the 256 points WE of spontaneous EEG and the 32 points average WE of ERP evidently decreased.
小波熵分析结果表明，与正常睡眠组比较，睡眠剥夺组自发脑电的256点小波熵和事件相关电位的32点小波熵均值都显著降低。
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