Mathematics in Independent Component Analysis

290 Chapter 20. Signal Processing 86(3):603-623, 2006
[36] D. Lee, H. Seung, Algorithms for non-negative matrix factorization, in:
Advances in Neural Information Processing (Proc. NIPS 2000), Vol. 13, MIT
Press, 2000, pp. 556–562.
[37] F. Theis, P. Georgiev, A. Cichocki, Robust overcomplete matrix recovery for
sparse sources using a generalized hough transform, in: Proc. ESANN 2004,
d-side, Evere, Belgium, Bruges, Belgium, 2004, pp. 343–348.
[38] P. Bradley, O. Mangasarian, k-plane clustering, Journal of Global Optimization
16 (1) (2000) 23–32.
[39] C. D. Luca, Physiology and mathematics of myoelectric signals, IEEE
Transactions on Biomedical Engineering 26 (6) (1979) 313–325.
[40] C. D. Luca, R. LeFever, M. McCue, A. Xenakis, Control scheme governing
concurrently active human motor units during voluntary contractions, Journal
of Physiology 329 (1982) 129–142.
[41] S. Amari, A. Cichocki, H. Yang, A new learning algorithm for blind signal
separation, Advances in Neural Information Processing Systems 8 (1996) 757–
763.
[42] D. Xu, J. Principe, J. F. III, H.-C. Wu, A novel measure for independent
component analysis (ICA), in: Proc. ICASSP 1998, Vol. 2, Seattle, 1998, pp.
1161–1164.
[43] D. Tjøstheim, Measures of dependence and tests of independence, Statistics 28
(1996) 249–282.
[44] R. Duda, P. Hart, D. Stork, Pattern classification, 2nd Edition, Wiley, New
York, 2001.
[45] F. Theis, S. Amari, Postnonlinear overcomplete blind source separation using
sparse sources, in: Proc. ICA 2004, Vol. 3195 of Lecture Notes in Computer
Science, Granada, Spain, 2004, pp. 718–725.
[46] P. Zhou, Z. Erim, W. Rymer, Motor unit action potential counts in surface
electrode array EMG, in: Proc. IEEE EMBS 2003, Cancun, Mexico, 2003, pp.
2067–2070.
[47] B. Freriks, H. Hermens, European Recommendations for
surface electromyography, results of the SENIAM project, Roessingh Research
and Development b.v. (CD-ROM), 1999.
29