基于CEEMD小波包算法的降噪方法研究

针对脑电信号易受噪声干扰的特性，提出一种使用CEEMD小波包对脑电信号进行降噪的方法。首先对脑电信号进行CEEMD分解，得到一组固有模态函数分量（IMF），然后对包含噪声的IMF分量采用小波包阈值降噪，同时保留信号的低频IMF分量，最后将使用小波包阈值降噪的IMF分量和保留的IMF分量进行累加重构，从而得到最终降噪后的脑电信号。仿真结果表明采用CEEMD小波包对脑电信号进行降噪，在抑制噪声的同时，还有效地保留了脑电信号的细节特性，达到良好的去噪特性。

A Denoising Method Based on CEEMD Wavelet Packet

Due to the characteristics of EEG is easy to be disturbed by noise, a method of the denoising EEG using CEEMD wavelet packet is proposed. Firstly, the EEG is decomposed by CEEMD to get a set of intrinsic mode function(IMF) components. Then the IMF component containing noise is denoised by wavelet packet threshold while the low-frequency IMF component of the signal is retained. Finally, the IMF components denoised by wavelet packet threshold and the reserved IMF components are accumulated and reconstructed to obtain the EEG after noise reduction. The experimental result shows that denoising of EEG using CEEMD wavelet packet can retain effectively the detailed characteristics of EEG when restraining noise， so as to achive good denoising performance.