摘要： 以经验模态分解(EMD)为理论基础，提出一种相似波形加权匹配的方法，对脑电信号(EEG)端点进行延拓，改善EMD分解过程中存在的端点效应，利用延拓后的EMD方法对EEG进行去噪。基于美国加州理工学院数据库中EEG的仿真结果表明，延拓后的EMD方法可有效去除EEG波形中的噪声部分，使EEG的特征更明显。

关键词: Hilbert-Huang变换, 脑电信号, 经验模态分解, 端点效应, 去噪

Abstract: This paper uses the Empirical Mode Decomposition(EMD) method as the theoretical basis. A new method based on weighted similar waveform which can improve the end effects in the processing of EMD effectively. It uses the new method to denoise the Electroence- phalogram(EEG) signals. Simulation results based on the EEG database of California Institute of Technology show the improved method can effectively remove the noise of the EEG wave, and makes the characteristics of EEG more obvious.

Key words: Hilbert-Huang Transform(HHT), Electroencephalogram(EEG), Empirical Mode Decomposition(EMD), end effect, denoising

中图分类号: 

• TP39