Improving empirical mode decomposition with an optimized piecewise cubic Hermite interpolation method

2012 International Conference on Systems and Informatics, ICSAI 2012

Volumn , Issue , 2012, Pages 1698-1701

  Zhu, Weifang ^a   Zhao, Heming ^a   Chen, Xiaoping ^a  

^a SOOCHOW UNIVERSITY   (China)

Author keywords

Empirical mode decomposition (EMD); envelope fitting; optimization; piecewise cubic Hermite interpolation

Indexed keywords

ADAPTIVE METHODS; CHAOS PARTICLE SWARM OPTIMIZATIONS; CUBIC HERMITE; CUBIC HERMITE INTERPOLATION; CUBIC SPLINE; EMPIRICAL MODE DECOMPOSITION; ENVELOPE FITTING; FITTING METHOD; LOWER ENVELOPES; NON-STATIONARY TIME SERIES; NUMERICAL EXPERIMENTS; PIECE-WISE;

INFORMATION SCIENCE; INTERPOLATION; OPTIMIZATION;

SIGNAL PROCESSING;

EID: 84864199924     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSAI.2012.6223368     Document Type: Conference Paper

References (12)

1. N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," Proc. R. Soc. London A, vol.454, pp.903-995, 1998.
2. Y. Zhong, S. Qin, B. Tang, "Research on a new transform method of a vibration signal," Libration Engineering Journal, vol.15, no.2, pp.233-238, 2002.
3. N. Bi, Q. Y. Sun, D. R. Huang, Z. H. Yang, J. W. Huang, "Robust image watermarking based on multiband wavelets and empirical mode decomposition," IEEE Trans. Image Process., vol.16, no.8, pp.1956-1966, 2007.
4. M. K. I. Molla, K. Hirose, "Signal-mixuture audio source separation by subspace decomposition of Hilbert spectrum," IEEE Trans. Speech Audio Process., vol.15, no.3, pp.893-900, 2007.
5. B. V. Manel, B. W. Weng, E. B. Kenneth, "ECG signal denoising and baseline wander correction based on the empirical mode decomposition," Computers in Biology and Medicine, vol.38, no.1, pp.1-13, 2008.
6. Q. H. Chen, N. E. Huang, S. Riemenschneider, Y. S. Xu, "A B-spline approach for empirical mode decompositions," Adv. Comp. Math., vol.24, pp.171-195, 2006.
7. Z. G. Xu, B. X. Huang, K. W. Li, "An alternative envelope approach for empirical mode decomposition," Digit. Signal Process., vol.20, pp.77-84, 2010.
8. Y. Kopsinis, S. McLaughlin, "Investigation and performance enhancement of the empirical mode decomposition method based on a heuristic search optimization approach," IEEE Trans. Signal Process., vol.56, no.1, pp.1-13, 2008.
9. S. R. Qin, Y. M. Zhong, "A new envelope algorithm of Hilbert-Huang transform," Mech. Syst. Signal Pr., vol.20, pp.1941-1952, 2006.
10. H. Akima, "New method of interpolation and smoothing curve fitting based on local procedures," JACM, vol.17, no.4, pp.589-602, 1970.
11. S. Gao, J. Y. Yang, "Research on chaos particle swarm optimization algorithm," Pattern Recognition and Artificial Intelligence, vol.19, no.2, pp.266-270, 2006.
12. G. B. Moody, R. G. Mark, A. L. Goldberger, "PhysioNet: a web-based resource for the study of physiologic signals," IEEE Eng. Med. Biol. Mag., vol.20, no.3, pp.70-75, 2001.