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Proceedings Paper

Learning in large optical networks
Author(s): Yong Qiao; Demetri Psaltis
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Paper Abstract

In a holographic optical learning network, the decay of multiply exposed holographic interconnections can adversely affect the training of the network. A new dynamic photorefractive holographic memory is described that allows an arbitrarily long sequence of adaptations by rejuvenating decayed holograms with a simple all-optical feedback loop.

Paper Details

Date Published: 16 September 1992
PDF: 3 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140042
Show Author Affiliations
Yong Qiao, California Institute of Technology (United States)
Demetri Psaltis, California Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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