关键词: 经验模态分解, 奇异谱分析, 本征模态函数

Abstract:

We propose an  empirical mode decomposition (EMD) de-noising method based on singular spectrum analysis (SA). Firstly, noisy signals are decomposed into several intrinsic mode functions (IMF) by the EMD in this method. The first IMF is regarded as high-frequency noise and the noise energy included in other IMFs can be estimated. Then, the ratio of signal energy in each IMF can be calculated. Secondly, the SSA is implemented on each IMF with proper window length and parts of proper singular value decomposition (SVD) components are selected to reconstruct the IMF according to the ratio of signal energy in each IMF. Finally, the denoised signals are obtained by adding all the reconstructed IMF and the residue. Compared with the wavelet soft threshold method, the EMD soft threshold method and the EMD filter method, the proposed method is superior to other methods as a whole, so it is an effective signal de-noising method.

Key words: empirical mode decomposition, singular spectrum analysis, intrinsic mode function