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Atick et al., 1992
Atick, J. J., Li, Z., and Redlich, A. N. (1992).
Understanding retinal color coding from first principles.
Neural Computation, 4:559-572.

Barlow et al., 1989
Barlow, H. B., Kaushal, T. P., and Mitchison, G. J. (1989).
Finding minimum entropy codes.
Neural Computation, 1(3):412-423.

Barrow, 1987
Barrow, H. G. (1987).
Learning receptive fields.
In Proceedings of the IEEE 1st Annual Conference on Neural Networks, volume IV, pages 115-121. IEEE.

Deco and Obradovic, 1996
Deco, G. and Obradovic, D. (1996).
An information-theoretic approach to neural computing.
Springer, New York.

Field, 1994
Field, D. J. (1994).
What is the goal of sensory coding?
Neural Computation, 6:559-601.

Földiák, 1990
Földiák, P. (1990).
Forming sparse representations by local anti-Hebbian learning.
Biological Cybernetics, 64:165-170.

Lindstädt, 1993
Lindstädt, S. (1993).
Comparison of two unsupervised neural network models for redundancy reduction.
In Mozer, M. C., Smolensky, P., Touretzky, D. S., Elman, J. L., and Weigend, A. S., editors, Proc. of the 1993 Connectionist Models Summer School, pages 308-315. Hillsdale, NJ: Erlbaum Associates.

Linsker, 1986a
Linsker, R. (1986a).
From basic network principles to neural architecture: Emergence of orientation-selective cells.
Proc. Natl. Acad. Sci. USA, 83:8779-8783.

Linsker, 1986b
Linsker, R. (1986b).
From basic network principles to neural architecture: Emergence of spatial-opponent cells.
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Linsker, 1988
Linsker, R. (1988).
Self-organization in a perceptual network.
IEEE Computer, 21:105-117.

MacKay and Miller, 1990
MacKay, D. J. C. and Miller, K. D. (1990).
Analysis of Linsker's simulation of Hebbian rules.
Neural Computation, 2:173-187.

Miller, 1994
Miller, K. D. (1994).
A model for the development of simple cell receptive fields and the ordered arrangement of orientation columns through activity-dependent competition between on- and off-center inputs.
Journal of Neuroscience, 14(1):409-441.

Rubner and Schulten, 1990
Rubner, J. and Schulten, K. (1990).
Development of feature detectors by self-organization: A network model.
Biological Cybernetics, 62:193-199.

Rubner and Tavan, 1989
Rubner, J. and Tavan, P. (1989).
A self-organization network for principal-component analysis.
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Schmidhuber, 1992
Schmidhuber, J. (1992).
Learning factorial codes by predictability minimization.
Neural Computation, 4(6):863-879.

Schmidhuber, 1993
Schmidhuber, J. (1993).
Netzwerkarchitekturen, Zielfunktionen und Kettenregel. Habilitationsschrift, Institut für Informatik, Technische Universität München.

Schmidhuber, 1994
Schmidhuber, J. (1994).
Neural predictors for detecting and removing redundant information.
In Cruse, H., Dean, J., and Ritter, H., editors, Adaptive Behavior and Learning, number 9, pages 135-145. Center for Interdisciplinary Research, Universität Bielefeld.

Juergen Schmidhuber 2003-02-17

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