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Issue No.06 - Nov.-Dec. (2011 vol.13)
pp: 42-51
Dan Chen , China University of Geosciences
Lizhe Wang , Indiana University
Gaoxiang Ouyang , Yanshan University, Qinhuangdao, China
Xiaoli Li , Yanshan University, Qinhuangdao, China
<p>Although the ensemble empirical mode decomposition (EEMD) method and Hilbert-Huang transform (HHT) offer an unrivaled opportunity to understand neural signals, the EEMD algorithm's complexity and neural signals' massive size have hampered EEMD application. However, a new approach using a many-core platform has proven both efficient and effective for massively parallel neural signal processing.</p>
Parallel processing, GPGPU, CUDA, many-core platform, neural signal analysis, EEG, epilepsy
Dan Chen, Lizhe Wang, Gaoxiang Ouyang, Xiaoli Li, "Massively Parallel Neural Signal Processing on a Many-Core Platform", Computing in Science & Engineering, vol.13, no. 6, pp. 42-51, Nov.-Dec. 2011, doi:10.1109/MCSE.2011.20
1. S. Sanei and J. Chambers, EEG Signal Processing, John Wiley & Sons, 2007, pp. 35–50.
2. Z.H. Wu and N.E. Huang, "Ensemble Empirical Mode Decomposition: A Noise Assisted Data Analysis Method," Advances in Adaptive Data Analysis, vol. 1, no. 1, 2009, pp. 1–41.
3. I.J. Rampil and R.S. Matteo, "Changes in EEG Spectral Edge Frequency Correlate with the Hemodynamic Response to Laryngoscopy and Intubation," Anesthesiology, vol. 67, no. 1, 1987, pp. 139–42.
4. X.L. Li et al., "Analysis of Depth of Anaesthesia with Hilbert-Huang Spectral Entropy," Clinical Neurophysiology, vol. 119, no. 11, 2008, pp. 2465–2475.
5. N.E. Huang et al., "The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis," Proc. Royal Society London, vol. 454, Nabu Press, 1998, pp. 903–95.
6. L. Wang et al., "Cloud Computing: A Perspective Study," New Generation Computing, vol. 28, no. 2, 2010, pp. 137–146.
7. V. Kindratenko, G.K. Thiruvathukal, and S. Gottlieb, "High-Performance Computing Applications on Novel Architectures," Computing in Science & Eng., vol. 10, no. 6, 2008, pp. 13–15.
8. O. Schenk, M. Christena, and H. Burkharta, "Algorithmic Performance Studies on Graphics Processing Units," J. Parallel and Distributed Computing, vol. 68, no. 10, 2008, pp. 1360–1369.
9. J.A. Wilson and J.C. Williams, "Massively Parallel Signal Processing Using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction," Front Neuroengineering, vol. 2, no. 11, 2009;
10. D. Chen et al., "Synchronization in Federation Community Networks," J. Parallel and Distributed Computing, vol. 70, no. 2, 2010, pp. 144–159.
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