Abstract

Architectures for partitioning optoelectronic analogs of neural nets into input-output and internal groups to form a multilayered net capable of self-organization, self-programming, and learning are described. The architectures and implementation ideas given describe a class of optoelectronic neural net modules that, when interfaced to a conventional computer controller, can impart to it artificial intelligence attributes.

© 1987 Optical Society of America

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