Empirical mode decomposition based soft-thresholding

Inspired by the wavelet soft thresholding principle, shrinkage methods suited for the thresholding of the decomposition modes resulting from applying EMD to a signal are developed in this paper. We show, that although a direct application of this principle is not feasible in the EMD case, it can be appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. Moreover, the SCAD thresholding rule is also incorporated and an iterative soft thresholding procedure is proposed which leads to enhanced denoising performance.

[1]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[2]  Tang Jing-tian,et al.  Hilbert-Huang Transform for ECG De-Noising , 2007, 2007 1st International Conference on Bioinformatics and Biomedical Engineering.

[3]  Norden E. Huang,et al.  STATISTICAL SIGNIFICANCE TEST OF INTRINSIC MODE FUNCTIONS , 2010 .

[4]  Steve McLaughlin,et al.  Investigation and Performance Enhancement of the Empirical Mode Decomposition Method Based on a Heuristic Search Optimization Approach , 2008, IEEE Transactions on Signal Processing.

[5]  Gabriel Rilling,et al.  EMD Equivalent Filter Banks, from Interpretation to Applications , 2005 .

[6]  Yannis Kopsinis.  EMPIRICAL MODE DECOMPOSITION BASED DENOISING TECHNIQUES , 2008 .

[7]  Sergios Theodoridis,et al.  Pattern Recognition , 1998, IEEE Trans. Neural Networks.

[8]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[9]  Jean-Christophe Cexus,et al.  Denoising via empirical mode decomposition , 2006 .

[10]  Steve McLaughlin,et al.  Improved EMD Using Doubly-Iterative Sifting and High Order Spline Interpolation , 2008, EURASIP J. Adv. Signal Process..

[11]  Peiwen Que,et al.  Noise suppression and flaw detection of ultrasonic signals via empirical mode decomposition , 2007 .

[12]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.