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Computational and Mathematical Methods in Medicine
Volume 2016 (2016), Article ID 8301962, 9 pages
http://dx.doi.org/10.1155/2016/8301962
Research Article

Improved CEEMDAN and PSO-SVR Modeling for Near-Infrared Noninvasive Glucose Detection

School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Received 14 April 2016; Revised 18 July 2016; Accepted 27 July 2016

Academic Editor: Thomas Desaive

Copyright © 2016 Xiaoli Li and Chengwei Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Xiaoli Li and Chengwei Li, “Improved CEEMDAN and PSO-SVR Modeling for Near-Infrared Noninvasive Glucose Detection,” Computational and Mathematical Methods in Medicine, vol. 2016, Article ID 8301962, 9 pages, 2016. doi:10.1155/2016/8301962