3.8 Blind source separation via ica: the team and thanks

Blind source separation via ica

The team and thanks

The team

• Akshay Dayal, ECE Department, Akshay.Dayal@rice.edu
• Mark Eastaway, ECE Department, Mark.Eastaway@rice.edu
• Angela Qian, ECE Department, Angela.Qian@rice.edu
• John Steinbauer, ECE Department, John.J.Steinbauer@rice.edu

Thanks and recognition

The team would also like to thank Professor Richard Barniuk and Mark Davenport, who helped jumpstart us on our project. We also would like to thank Michael Dye and the Rice University ERC for providing the microphone hardware we used to implement our project.

References

• Gävert, H., Hurri, J., Särelä, J., and Hyvärinen, A. (2005). The FastICA Package for MATLAB . Free Software Foundation.
• Hyvarinen, A. and Erkki, O.(2000). Independent Component Analysis: Algorithms and Applications . Neural Networks, 13(4-5): 411-430.
• Cichocki, A. (2004). Blind Signal Processing Methods for AnalyzingMultichannel Brain Signals. International Journal of Bioelectromagnetism 2004, Vol. 6, No. 1 .
• Jourjine, A., Rickard, S., Yilmaz, O. (2000). Blind Separation of Disjoint Orthogonal Signals: Demixing N Sources from 2 Mixtures. IEEE.
• Fiori, S. (1999). Entrophy Optimization by the PFANN Network: Application to Blind Source Separation. Network: Cornput. Neural Syst. 10 171-186.
• Meyer-Base, A., Gruber, P., Theis, F., and Foo, S. (2005). Blind Source Separation Based on Self-Organizing Neural Network. Science Direct.