Table of Contents
Advances in Artificial Neural Systems
Volume 2012, Article ID 962105, 13 pages
http://dx.doi.org/10.1155/2012/962105
Research Article

Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms

1400 Dirac Science Library, Florida State University, Tallahassee, FL 32306-4120, USA
2Department for Informatics, Research Unit for Database Systems, University of Munich, Oettingenstraße 67, 80538 Munich, Germany
3Klinikum rechts der Isar der TUM, Ismaninger Straße 22, 81675 Munich, Germany
4Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany

Received 14 February 2012; Accepted 1 April 2012

Academic Editor: Juan Manuel Gorriz Saez

Copyright © 2012 Claudia Plant et al. 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.

Linked References

  1. O. Sporns, “The human connectome: a complex network,” Annals of the New York Academy of Sciences, vol. 1224, no. 1, pp. 109–125, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Hyvärinen, “Fast and robust fixed-point algorithms for independent component analysis,” IEEE Transactions on Neural Networks, vol. 10, no. 3, pp. 626–634, 1999. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley & Sons, New York, NY, USA, 2001.
  4. P. M. Rasmussen, M. Mørup, L. K. Hansen, and S. M. Arnfred, “Model order estimation for independent component analysis of epoched EEG signals,” in Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS '08), pp. 3–10, January 2008. View at Scopus
  5. C. J. James and C. W. Hesse, “Independent component analysis for biomedical signals,” Physiological Measurement, vol. 26, no. 1, pp. R15–R39, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Hyvärinen and E. Oja, “Independent component analysis: algorithms and applications,” Neural Networks, vol. 13, no. 4-5, pp. 411–430, 2000. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Himberg and A. Hyvärinen, “Icasso: software for investigating the reliability of ica estimates by clustering and visualization,” in Proceedings of the IEEE Workshop on Neural Networks for Signal Processing (NNSP '03), pp. 259–268, 2003.
  8. F. Meinecke, A. Ziehe, M. Kawanabe, and K. R. Müller, “A resampling approach to estimate the stability of one-dimensional or multidimensional independent components,” IEEE Transactions on Biomedical Engineering, vol. 49, no. 12, pp. 1514–1525, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. G. Qian, “Computing minimum description length for robust linear regression model selection,” in Proceedings of the Pacific Symposium on Biocomputing, pp. 314–325, 1999.
  10. S. R. Rao, H. Mobahi, A. Y. Yang, S. S. Sastry, and Y. Ma, “Natural image segmentation with adaptive texture and boundary encoding,” in Proceedings of the Asian Conference on Computer Vision (ACCV '09), vol. 5994 of Lecture Notes in Computer Science, pp. 135–146, 2009.
  11. T. Wekel and O. Hellwich, “Selection of an optimal polyhedral surface model using the minimum description length principle,” in Proceedings of the 32nd Symposium of the German Association for Pattern Recognition (DAGM '10), vol. 6376 of Lecture Notes in Computer Science, pp. 553–562, 2010.
  12. J. Sun, C. Faloutsos, S. Papadimitriou, and P. S. Yu, “GraphScope: parameter-free mining of large time-evolving graphs,” in Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '07), pp. 687–696, August 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. D. Pelleg and A. W. Moore, “X-means: extending k-means with efficient estimation of the number of clusters,” in Proceedings of the 17th International Conference on Machine Learning (ICML '00), pp. 727–734, 2000.
  14. C. Böhm, C. Faloutsos, J. Y. Pan, and C. Plant, “Robust information-theoretic clustering,” in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '06), pp. 65–75, August 2006. View at Scopus
  15. C. Böhm, C. Faloutsos, and C. Plant, “Outlier-robust clustering using independent components,” in Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD '08), pp. 185–198, June 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. C. Böhm, K. Haegler, N. S. Müller, and C. Plant, “CoCo: coding cost for parameter-free outlier detection,” in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '09), pp. 149–157, July 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. P. Gruber, F. Theis, A. Tome, and E. Lang, “Automatic denoising using local independent component analysis,” in Proceedings of the 4th International ICSC Symposium on Engineering of Intelligent Systems (EIS '04), 2004.
  18. A. Barron, J. Rissanen, and B. Yu, “The Minimum Description Length Principle in Coding and Modeling,” IEEE Transactions on Information Theory, vol. 44, no. 6, pp. 2743–2760, 1998. View at Google Scholar · View at Scopus
  19. T. C. M. Lee, “Regression spline smoothing using the minimum description length principle,” Statistics and Probability Letters, vol. 48, no. 1, pp. 71–82, 2000. View at Google Scholar · View at Scopus
  20. T. W. Lee, M. S. Lewicki, and T. J. Sejnowski, “ICA mixture models for unsupervised classification of non-Gaussian classes and automatic context switching in blind signal separation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1078–1089, 2000. View at Publisher · View at Google Scholar · View at Scopus
  21. A. Wismüller, O. Lange, D. R. Dersch et al., “Cluster analysis of biomedical image time-series,” International Journal of Computer Vision, vol. 46, no. 2, pp. 103–128, 2002. View at Publisher · View at Google Scholar · View at Scopus