Grouping and Selecting Singular Spectrum Analysis Components for Denoising Via Empirical Mode Decomposition Approach-Reference-Cited by-同舟云学术

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Grouping and Selecting Singular Spectrum Analysis Components for Denoising Via Empirical Mode Decomposition Approach

Published:2018-06-08 Issue:1 Volume:38 Page:356-370
ISSN:0278-081X
Container-title:Circuits, Systems, and Signal Processing
language:en
Short-container-title:Circuits Syst Signal Process

Author:

Lin Peiru,Kuang Weichao,Liu Yuwei,Ling Bingo Wing-Kuen

Funder

National Nature Science Foundation of China

Guangdong Higher Education Engineering Technology Research Center for Big Data on Manufacturing Knowledge Patent

Natural Science Foundation of Guangdong Province China

Science and Technology Planning Project of Guangdong Province China

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Signal Processing

Link

http://link.springer.com/article/10.1007/s00034-018-0861-1/fulltext.html

Reference29 articles.

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2. N. Alharbi, Z. Ghodsi, H. Hassani, Noise correction in gene expression data: a new approach based on subspace method. Math. Methods Appl. Sci. 39(13), 3750–3757 (2016)

3. A. Antoniadis, J. Bigot, T. Sapatinas, Wavelet estimators in nonparametric regression: a comparative simulation study. J. Stat. Softw. 6, 1–83 (2001)

4. A.O. Boudraa, J.C. Cexus, EMD-based signal filtering. IEEE Trans. Instrum. Meas. 56(6), 2196–2202 (2007)

5. A.O. Boudraa, J.C. Cexus, Z. Saidi, EMD-based signal noise reduction. Int. J. Inf. Commun. Eng. 1(1), 33–37 (2004)

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