**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**31532

##### Optimizing Approach for Sifting Process to Solve a Common Type of Empirical Mode Decomposition Mode Mixing

**Authors:**
Saad Al-Baddai,
Karema Al-Subari,
Elmar Lang,
Bernd Ludwig

**Abstract:**

**Keywords:**
Empirical mode decomposition,
mode mixing,
sifting
process,
over-sifting.

**Digital Object Identifier (DOI):**
doi.org/10.5281/zenodo.1131231

**References:**

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[2] V. D. Calhoun, T. Adali, L. K. Hansen, J. Larsen, and J. J. Pekar, “ICA of functional MRI data: An overview,” in in Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation, 2003, pp. 281–288.

[3] A. Cichocki, S. Amari, K. Siwek, T. Tanaka, and A. H. P. et al., “ICALAB Toolboxes,” 2007. (Online). Available: http: //www.bsp.brain.riken.jp/ICALAB.

[4] P. Common and C. Jutten, Handbook of Blind Source Separation: Independent Component Analysis and its Applications. Academic Press, 2010.

[5] S. Al-Baddai, K. Al-Subari, A. Tomé, J. J. Solé-Casals, and E. Lang, “A green’s function-based bi-dimensional empirical mode decomposition,” Information Sciences, vol. 348, pp. 305–321, 2016.

[6] K. Al-Subari, S. Al-Baddai, A. Tomé, G. Volberg, R. Hammwöhner, and E. Lang, “Ensemble empirical mode decomposition analysis of EEG data collected during a contour integration task,” PLoS ONE, vol. 10, no. 4, p. e0119489, 04 2015.

[7] K. Al-Subari, S. Al-Baddai, A. Tomé, M. Goldhacker, R. Faltermeier, and E. Lang, “Emdlab:a toolbox for analysis of single-trial eeg dynamics using empirical mode decomposition,” Journal of Neuroscience Methods, vol. 253C, pp. 193–205, 07 2015.

[8] E. W. Lang, R. Schachtner, D. Lutter, D. Herold, A. Kodewitz, F. Blöchl, F. J. Theis, I. R. Keck, J. M. G. Sáez, P. G. Vilda, and A. M. Tomé, Exploratory Matrix Factorization Techniques for Large Scale Biomedical Data Sets. Bentham Science Publishers, 2010.

[9] N. Attoh-Okine, K. Barner, D. Bentil, and R. Zhang, “The Empirical Mode Decomposition and the Hilbert-Huang Transform,” EURASIP J. Advances in Signal Processing, 2008.

[10] Z. Wu and N. E. Huang, “Ensemble Empirical Mode Decomposition: a noise-assisted data analysis method,” Adv. Adaptive Data Analysis, vol. 1(1), pp. 1–41, 2009.

[11] Z. Wu, N. E. Huang, and X. Chen, “The Multidimensional Ensemble Empirical Mode Decomposition Method,” Adv. Adaptive Data Analysis, vol. 1, pp. 339–372, 2009.

[12] P. Flandrin, G. Rilling, and P. Goncalves, “Empirical mode decomposition as afilter bank,” Signal Processing Letters, IEEE, vol. 11(2), pp. 112–114, 2004.

[13] Z. Wu1 and N. E. Huang, “A study of the characteristics of white noise using the empirical mode decomposition method,” in Proceedings of the Royal Society, vol. 460, 2004, pp. 1597–1611.