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.
Older PCA / ICA papers available on-line
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"
A simplified neuron model as a principal component
analyzer. J. Math. Biol. 15, pp. 267-273 (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. 69-84 (1985).
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 Hebbian-like Learning Rules.
Signal Processing 64 64}, pp. 301 - 313 (1998).
Hyvärinen, A. and Oja, E.: A
Fast Fixed-Point Algorithm for Independent Component Analysis. Neural
Computation 9, pp. 1483 - 1492 (1997).
Hyvärinen, A. and Oja, E.: One-Unit
Learning Rules for Independent Component Analysis. Advances in Neural
Information Processing Systems 9, MIT Press, pp. 480--486 (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 anti-Hebbian 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 ICANN-95, 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
Erkki Oja, professor
Laboratory of Computer
and Information Science
P.O.Box 5400 (Konemiehentie 2)