Bibliography

1

H. Attias.
Independent factor analysis.
Neural Computation, 11(4):803-851, 1999.

2

O. Bermond and J.-F. Cardoso.
Approximate likelihood for noisy mixtures.
In Proc. ICA'99, pp. 325-330, Aussois, France, 1999.

3

J.-F. Cardoso.
Multidimensional independent component analysis.
In Proc. ICASSP'98, pp. 1941-1944, Seattle, WA, 1998.

4

A. Hyvärinen and P. O. Hoyer.
Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces.
Neural Computation, 2000.
In press.

5

A. Hyvärinen and E. Oja.
A fast fixed-point algorithm for independent component analysis.
Neural Computation, 9(7):1483-1492, 1999.

6

H. Lappalainen.
Nonlinear independent component analysis using ensemble learning: Theory.
In Proc. ICA 2000.
Submitted.

7

H. Lappalainen.
Ensemble learning for independent component analysis.
In Proceedings of the ICA'99, pp. 7-12, Aussois, France, 1999.

8

H. Lappalainen, X. Giannakopoulos, A. Honkela, and J. Karhunen.
Nonlinear independent component analysis using ensemble learning: Experiments and discussion.
In Proc. ICA 2000.
Submitted.

9

Éric Moulines, J.-F. Cardoso, and E. Gassiat.
Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models.
In Proc. ICASSP'97, pp. 3617-3620, Munich, Germany, 1997.

10

R. Vigário, V. Jousmäki, M. Hämäläinen, R. Hari, and E. Oja.
Independent component analysis for identification of artifacts in magnetoencephalographic recordings.
In Advances in Neural Information Processing Systems 10, pp. 229-235. MIT Press, 1998.