TY - JOUR
T1 - Development of EMD-based denoising methods inspired by wavelet thresholding
AU - Kopsinis, Yannis
AU - McLaughlin, Stephen
PY - 2009/4
Y1 - 2009/4
N2 - One of the tasks for which empirical mode decomposition (EMD) is potentially useful is nouparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can he appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance.
AB - One of the tasks for which empirical mode decomposition (EMD) is potentially useful is nouparametric signal denoising, an area for which wavelet thresholding has been the dominant technique for many years. In this paper, the wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show that although a direct application of this principle is not feasible in the EMD case, it can he appropriately adapted by exploiting the special characteristics of the EMD decomposition modes. In the same manner, inspired by the translation invariant wavelet thresholding, a similar technique adapted to EMD is developed, leading to enhanced denoising performance.
UR - https://www.scopus.com/pages/publications/63449122839
U2 - 10.1109/TSP.2009.2013885
DO - 10.1109/TSP.2009.2013885
M3 - Article
SN - 1053-587X
VL - 57
SP - 1351
EP - 1362
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 4
ER -