Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance. (15th May 2008)

• Record Type: Journal Article
• Authors: Pinle Pinle, Qin Qin; Yan Yan, Lin Lin; Ming Ming, Chen Chen
• Other Names: Attoh-Okine Attoh-Okine Nii Nii Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-05-15
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/526038
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by using wavelet denoising method to avoid the mode mixture in the subsequent EMD procedure. Because traditional wavelet threshold denoising may exhibit pseudo-Gibbs phenomena in the neighborhood of discontinuities, we make use of translation invariance algorithm to suppress the artifacts. Then the processed signal is decomposed into intrinsic mode functions (IMFs) by EMD. The numerical results show that the proposed method is able to effectively avoid the mode mixture and retain the useful information.