MEMD-Based Filtering Using Interval Thresholding and Similarity Measure between Pdf of IMFs

Huan HAO  Huali WANG  Weijun ZENG  Hui TIAN  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E99-A   No.2   pp.643-646
Publication Date: 2016/02/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E99.A.643
Type of Manuscript: LETTER
Category: Digital Signal Processing
multivariate empirical mode decomposition (MEMD),  interval thresholding,  probability density functions,  

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This paper presents a novel MEMD interval thresholding denoising, where relevant modes are selected by the similarity measure between the probability density functions of the input and that of each mode. Simulation and measured EEG data processing results show that the proposed scheme achieves better performance than other traditional denoisings.