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Detection singularity value of character wave in epileptic EEG by wavelet

机译:小波检测癫痫脑电图中字符波的奇异性值

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Human epilepsy is an intrinsic brain pathology, whose activity varies depending on the type of epilepsy and is characterized by repetitive high-amplitude activity. The wavelet transform provides an important tool in signal analysis and feature extraction. The modulus maximum pair of the wavelet transform method is used to detect the singularity value of the sharps and spikes embedded in the background activities of the epilepsy electroencephalograph (EEG) signal. The wavelet transforms of singularities with fast oscillations have a particular behavior that is studied separately; they are measured from the modulus maxima of the wavelet transform. The efficacy of the proposed method has been tested with clinical EEG.
机译:人的癫痫是一种内在的脑病,其活动根据癫痫的类型而变化,其特征在于重复的高幅度活动。小波变换在信号分析和特征提取中提供了一个重要的工具。模数最大对小波变换方法用于检测嵌入在癫痫脑电图(EEG)信号的后台活动中嵌入的尖锐和尖峰的奇点值。快速振荡的奇点的小波变换具有单独研究的特定行为;它们是从小波变换的模量最大值测量的。所提出的方法的功效已用临床脑电图测试。

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