Erkki Oja:
Older PCA / ICA papers available online
The first list below contains some of my older PCA papers
which are often asked for, but may not be readily available.
I have scanned them into pdf files. Clicking the paper name should bring
the paper on your screen, from which you can print it.
The second list contains some more recent stuff on nonlinear PCA and ICA.
NOTE: The manuscripts themselves may not contain proper
bibliographic data (where and when they have been published).
Should you wish to cite one of the papers, please use the information
on the following list.

Papers on neural PCA and "Oja's rule"

Oja, E.:
A simplified neuron model as a principal component
analyzer. J. Math. Biol. 15, pp. 267273 (1982).

Oja, E. and Karhunen, J.:
On stochastic approximation of the
eigenvectors and eigenvalues of the expectation of a random matrix.
J. Math. Anal. Appl 106, pp. 6984 (1985).

Oja, E.:
Principal components, minor components, and linear
neural networks. Neural Networks 5, pp. 927  935 (1992).

Papers on nonlinear PCA and ICA

Hyvärinen, A. and Oja, E.: Independent
Component Analysis by General Nonlinear Hebbianlike Learning Rules.
Signal Processing 64 64}, pp. 301  313 (1998).

Hyvärinen, A. and Oja, E.: A
Fast FixedPoint Algorithm for Independent Component Analysis. Neural
Computation 9, pp. 1483  1492 (1997).

Hyvärinen, A. and Oja, E.: OneUnit
Learning Rules for Independent Component Analysis. Advances in Neural
Information Processing Systems 9, MIT Press, pp. 480486 (1997).

Oja, E.: The nonlinear PCA
learning rule in Independent Component Analysis (draft).
Neurocomputing 17, pp. 25  45 (1997).

Karhunen, J., Oja, E., Wang, L., Vigario, R., and Joutsensalo, J.: A class of neural networks for Independent
Component Analysis (draft). IEEE Trans. on Neural Networks
8, pp. 486  504 (1997).

Hyvärinen, A. and Oja, E.: Simple
neuron models for Independent Component Analysis. Int. J. Neural
Systems 7, pp. 671  687 (1996).

Oja, E. and Wang, L.:
Neural fitting: robustness by antiHebbian learning (draft).
Neurocomputing 12, pp. 155  170 (1996).

Oja, E. and Wang, L.:
Robust fitting by nonlinear neural units (draft). Neural
Networks 9, pp. 435  444 (1996).

Oja, E., Karhunen, J., Wang, L., and Vigario, R.:Principal
and independent components in neural networks  recent developments.
Proc. VII Italian Workshop on Neural Nets WIRN'95, May 18  20,
1995, Vietri sul Mare, Italy (1995).

Oja, E.:The nonlinear
PCA learning rule and signal separation  mathematical analysis. Helsinki
University of Technology, Laboratory of Computer and Information Science,
Report A26 (1995).

Oja, E.: PCA, ICA,
and nonlinear Hebbian learning. Proc. Int. Conf. on Artificial Neural
Networks ICANN95, Oct. 9  13, 1995, Paris, France, pp. 89  94 (1995).

Oja, E. and Karhunen, J.:Signal
separation by nonlinear Hebbian learning. In M. Palaniswami, Y. Attikiouzel,
R. Marks II, D. Fogel, and T. Fukuda (Eds.), Computational Intelligence
 a Dynamic System Perspective. New York: IEEE Press, pp. 83  97 (1995).

(More papers can be found on the home pages of the
members of the ICA
research group).
Erkki Oja, professor
Laboratory of Computer
and Information Science
P.O.Box 5400 (Konemiehentie 2)
FIN02015 HUT
Finland
Tel. +35804513265
Fax. +35804513277
EMail Erkki.Oja@hut.fi