基于经验模式分解的自适应去噪算法

Adaptive de-noising algorithm based on EMD

基于加性高斯白噪声在经验模式分解算法(Empirical Mode Decomposition,EMD)下的统计特性,提出了一种基于EMD的去噪算法。通过数值仿真,比较了提出的算法与小波域阈值去噪的性能。仿真结果表明,该算法与小波域阈值去噪的效果相似,而不用选择小波基,是一种自适应的去噪算法。

Based on the statistic features of uniformly distributed white noise using the Empirical Mode Decomposition（EMD）,an adaptive de-noising algorithm based on EMD is proposed.The numerical experiments are made between the Wavelet Threshold De-noise（WTD） and the adaptive method based on EMD.The results show that the adaptive method is similar to WTD,and it is no need to select a mother wavelet,it is adaptive to kinds of signals.