- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 525396, 6 pages
Variance Entropy: A Method for Characterizing Perceptual Awareness of Visual Stimulus
School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
Received 28 December 2011; Revised 22 March 2012; Accepted 23 March 2012
Academic Editor: Cheng-Hsiung Hsieh
Copyright © 2012 Meng Hu and Hualou Liang. 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.
- S. M. Pincus, “Approximate entropy as a measure of system complexity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 88, no. 6, pp. 2297–2301, 1991.
- J. S. Richman and J. R. Moorman, “Physiological time-series analysis using approximate and sample entropy,” American Journal of Physiology, vol. 278, no. 6, pp. H2039–H2049, 2000.
- D. E. Lake, J. S. Richman, M. Pamela Griffin, and J. Randall Moorman, “Sample entropy analysis of neonatal heart rate variability,” American Journal of Physiology, vol. 283, no. 3, pp. R789–R797, 2002.
- E. N. Bruce, M. C. Bruce, and S. Vennelaganti, “Sample entropy tracks changes in electroencephalogram power spectrum with sleep state and aging,” Journal of Clinical Neurophysiology, vol. 26, no. 4, pp. 257–266, 2009.
- S. Ramdani, B. Seigle, J. Lagarde, F. Bouchara, and P. L. Bernard, “On the use of sample entropy to analyze human postural sway data,” Medical Engineering and Physics, vol. 31, no. 8, pp. 1023–1031, 2009.
- M. Costa, A. L. Goldberger, and C. K. Peng, “Multiscale entropy analysis of complex physiologic time series,” Physical Review Letters, vol. 89, no. 6, Article ID 068102, 4 pages, 2002.
- M. Hu and H. Liang, “Adaptive multiscale entropy analysis of multivariate neural data,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 1, pp. 12–15, 2012.
- J. S. Richman, D. E. Lake, and J. R. Moorman, “Sample entropy,” Methods in Enzymology, vol. 384, pp. 172–184, 2004.
- M. Wilke, N. K. Logothetis, and D. A. Leopold, “Generalized flash suppression of salient visual targets,” Neuron, vol. 39, no. 6, pp. 1043–1052, 2003.
- P. Grassberger and I. Procaccia, “Estimation of the Kolmogorov entropy from a chaotic signal,” Physical Review A, vol. 28, no. 4, pp. 2591–2593, 1983.
- J. P. Eckmann and D. Ruelle, “Ergodic theory of chaos and strange attractors,” Reviews of Modern Physics, vol. 57, no. 3, pp. 617–656, 1985.
- S. Lu, X. Chen, J. K. Kanters, I. C. Solomon, and K. H. Chon, “Automatic selection of the threshold value r for approximate entropy,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 8, pp. 1966–1972, 2008.
- N. Rehman and D. P. Mandic, “Multivariate empirical mode decomposition,” Proceedings of the Royal Society A, vol. 466, no. 2117, pp. 1291–1302, 2010.
- M. Wilke, N. K. Logothetis, and D. A. Leopold, “Local field potential reflects perceptual suppression in monkey visual cortex,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 46, pp. 17507–17512, 2006.
- L. V. Hedges and I. Olkin, Statistical Methods for Meta-Analysis, Academic Press, Orlando, Fla, USA, 1985.