Multivariate techniques for preprocessing noisy data for source separation using ICA-Reference-Cited by-同舟云学术

Multivariate techniques for preprocessing noisy data for source separation using ICA

Published:2012-06 Issue:1-2 Volume:4 Page:32-40
ISSN:0975-0770
Container-title:International Journal of Advances in Engineering Sciences and Applied Mathematics
language:en
Short-container-title:Int J Adv Eng Sci Appl Math

Author:

Ramesh Babu P.,Narasimhan Shankar

Publisher

Springer Science and Business Media LLC

Link

http://link.springer.com/content/pdf/10.1007/s12572-012-0065-z.pdf

Reference25 articles.

1. Jutten, C., Herault, J.: Separation of sources-part I. Signal Process. 24, 1–10 (1991)

2. Vigário, R., Särelä, J., Jousmäki, V., Hämäläinen, M., Oja, E.: Independent component approach to the analysis of EEG and MEG recordings. IEEE Trans. Biomed. Eng. 47, 589–593 (2000)

3. Chen, J., Wang, X.Z.: A new approach to near-infrared spectral data analysis. J. Chem. Inf. Comput. Sci. 41, 992–1001 (2001)

4. Cichocki, A., Amari, S.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. Wiley, Chichester (2002)

5. Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. Advances in neural information processing (13), MIT press, Cambridge (2001)

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