Proceedings Paper
Architectures For A Continuous Level Neural Network Based On Alternating Orthogonal Projections| Format | Member Price | Non-Member Price |
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Paper Abstract
Optical processor architectures for various forms of the alternating projection neural network (APNN) are considered. Required iteration is performed by passive optical feedback using only free space and guided propagation. No electronics or slow optics (e.g. phase conjugators) are used. The processor can be taught a new training vector by viewing it only once.
Paper Details
Date Published: 3 May 1988
PDF: 3 pages
Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944105
Published in SPIE Proceedings Vol. 0882:
Neural Network Models for Optical Computing
Ravindra A. Athale; Joel Davis, Editor(s)
PDF: 3 pages
Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944105
Show Author Affiliations
Robert J Marks, University of Washington (United States)
Les E Atlas, University of Washington (United States)
Les E Atlas, University of Washington (United States)
Seho Oh, University of Washington (United States)
Kwan F Cheung, University of Washington (United States)
Kwan F Cheung, University of Washington (United States)
Published in SPIE Proceedings Vol. 0882:
Neural Network Models for Optical Computing
Ravindra A. Athale; Joel Davis, Editor(s)
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