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ISRN Signal Processing
Volume 2013 (2013), Article ID 218651, 17 pages
Extraction of Correlated Sparse Sources from Signal Mixtures
1Electrical Systems and Optics Division, Faculty of Engineering, The University of Nottingham, Nottingham NG7 2RD, UK
2Engineering Science Department, Ecological University of Bucharest, Bd. Vasile Milea nr. 1G, Sector 6, 061341 Bucharest, Romania
Received 6 November 2012; Accepted 3 December 2012
Academic Editors: S. Callegari, W.-L. Hwang, S. Lee, and P. Ramaswamy
Copyright © 2013 M. S. Woolfson 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.
- J. J. Rieta, F. Castells, C. Sánchez, V. Zarzoso, and J. Millet, “Atrial activity extraction for atrial fibrillation analysis using blind source separation,” IEEE Transactions on Biomedical Engineering, vol. 51, no. 7, pp. 1176–1186, 2004.
- L. Shoker, S. Sanei, and J. Chambers, “Artifact removal from electroencephalograms using a hybrid BSS-SVM algorithm,” IEEE Signal Processing Letters, vol. 12, no. 10, pp. 721–724, 2005.
- Z. Dawy, M. Sarkis, J. Hagenauer, and J. C. Mueller, “A novel gene mapping algorithm based on independent component analysis,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '05), vol. 5, pp. 381–384, Philadelphia, Pa, USA, March 2005.
- D. Nuzillard, S. Bourg, and J. M. Nuzillard, “Model-free analysis of mixtures by NMR using blind source separation,” Journal of Magnetic Resonance, vol. 133, no. 2, pp. 358–363, 1998.
- J. Y. Ren, C. Q. Chang, P. C. W. Fung, J. G. Shen, and F. H. Y. Chan, “Free radical EPR spectroscopy analysis using blind source separation,” Journal of Magnetic Resonance, vol. 166, no. 1, pp. 82–91, 2004.
- W. T. Zhang, S. T. Lou, and Y. L. Zhang, “Robust nonlinear power iteration algorithm for adaptive blind separation of independent signals,” Digital Signal Processing, vol. 20, no. 2, pp. 541–551, 2010.
- M. T. Özgen, E. E. Kuruoǧlu, and D. Herranz, “Astrophysical image separation by blind time-frequency source separation methods,” Digital Signal Processing, vol. 19, no. 2, pp. 360–369, 2009.
- Q. He, S. Su, and R. Du, “Separating mixed multi-component signal with an application in mechanical watch movement,” Digital Signal Processing, vol. 18, no. 6, pp. 1013–1028, 2008.
- A. Hyvärinen and E. Oja, “Independent component analysis: algorithms and applications,” Neural Networks, vol. 13, no. 4-5, pp. 411–430, 2000.
- V. Zarzoso and A. K. Nandi, “Blind separation of independent sources for virtually any source probability density function,” IEEE Transactions on Signal Processing, vol. 47, no. 9, pp. 2419–2432, 1999.
- M. Babaie-Zadeh, C. Jutten, and A. Mansour, “Sparse ICA via cluster-wise PCA,” Neurocomputing, vol. 69, no. 13–15, pp. 1458–1466, 2006.
- C. Chang, P. C. W. Fung, and Y. S. Hung, “On a sparse component analysis approach to BSS,” in International Conference on Independent Component Analysis and Blind Source Separation (ICA '06), pp. 765–772, Charleston, SC, USA, March 2006.
- P. D. O'Grady, B. A. Pearlmutter, and S. T. Rickard, “Survey of sparse and non-sparse methods in source separation,” International Journal of Imaging Systems and Technology, vol. 15, no. 1, pp. 18–33, 2005.
- F. J. Theis, A. Jung, C. G. Puntonet, and E. W. Lang, “Linear geometric ICA: fundamentals and algorithms,” Neural Computation, vol. 15, no. 2, pp. 419–439, 2003.
- P. Georgiev, F. Theis, and A. Cichocki, “Sparse component analysis and blind source separation of underdetermined mixtures,” IEEE Transactions on Neural Networks, vol. 16, no. 4, pp. 992–996, 2005.
- M. Davies and N. Mitianoudis, “Simple mixture model for sparse overcomplete ICA,” IEE Proceedings: Vision, Image and Signal Processing, vol. 151, no. 1, pp. 35–43, 2004.
- M. S. Woolfson, C. Bigan, J. A. Crowe, and B. R. Hayes-Gill, “Method to separate sparse components from signal mixtures,” Digital Signal Processing, vol. 18, no. 6, pp. 985–1012, 2008.
- Y. Sun, C. Ridge, F. Del Rio, A. J. Shaka, and J. Xin, “Postprocessing and sparse blind source separation of positive and partially overlapped data,” Signal Processing, vol. 91, no. 8, pp. 1838–1851, 2011.
- August 2012, http://www.cis.hut.fi/projects/ica/fastica/.
- “Database for the Identification of Systems (DaISy),” August 2012, http://homes.esat.kuleuven.be/~smc/daisy/.
- Y. Xiang, S. K. Ng, and V. K. Nguyen, “Blind separation of mutually correlated sources using precoders,” IEEE Transactions on Neural Networks, vol. 21, no. 1, pp. 82–90, 2010.
- W. Naanaa and J. M. Nuzillard, “Blind source separation of positive and partially correlated data,” Signal Processing, vol. 85, no. 9, pp. 1711–1722, 2005.