Self-organization in a perceptual network

The emergence of a feature-analyzing function from the development rules of simple, multilayered networks is explored. It is shown that even a single developing cell of a layered network exhibits a remarkable set of optimization properties that are closely related to issues in statistics, theoretical physics, adaptive signal processing, the formation of knowledge representation in artificial intelligence, and information theory. The network studied is based on the visual system. These results are used to infer an information-theoretic principle that can be applied to the network as a whole, rather than a single cell. The organizing principle proposed is that the network connections develop in such a way as to maximize the amount of information that is preserved when signals are transformed at each processing stage, subject to certain constraints. The operation of this principle is illustrated for some simple cases.<<ETX>>

[1]  P. B. Liebelt.  An Introduction To Optimal Estimation , 1967 .

[2]  D. Hubel,et al.  Ferrier lecture - Functional architecture of macaque monkey visual cortex , 1977, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  T. Wiesel,et al.  Functional architecture of macaque monkey visual cortex , 1977 .

[4]  D H Hubel,et al.  Brain mechanisms of vision. , 1979, Scientific American.

[5]  E. Oja.  Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.

[6]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[7]  R. Linsker,et al.  From basic network principles to neural architecture , 1986 .

[8]  R. Linsker.  From basic network principles to neural architecture (series) , 1986 .

[9]  R Linsker,et al.  From basic network principles to neural architecture: emergence of spatial-opponent cells. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Robin Sibson,et al.  What is projection pursuit , 1987 .

[11]  Ralph Linsker,et al.  Towards an Organizing Principle for a Layered Perceptual Network , 1987, NIPS.

[12]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[13]  Ralph Linsker,et al.  Computer simulation in brain science: Development of feature-analyzing cells and their columnar organization in a layered self-adaptive network , 1988 .

[14]  Teuvo Kohonen,et al.  Self-organization and associative memory: 3rd edition , 1989 .