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Renewal method of weight matrix in optical neural network| Format | Member Price | Non-Member Price |
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Paper Abstract
We proposed a new renewal method of the weights to realize a back propagation learning algorithm with a large number of iteration times in an optical neural network. The main purpose of this method is to use the limited dynamic range of an optical device widely. Since some weights displaying on the device are quickly saturated in the conventional method, the learning is not completed in many cases. The new technique can suppress saturation of the weights so that learning is completed. The computer simulation and the optical experiment are presented.
Paper Details
Date Published: 12 July 1993
PDF: 8 pages
Proc. SPIE 1806, Optical Computing, (12 July 1993); doi: 10.1117/12.147840
Published in SPIE Proceedings Vol. 1806:
Optical Computing
Andrey M. Goncharenko; Fedor V. Karpushko; George V. Sinitsyn; Sergey P. Apanasevich, Editor(s)
PDF: 8 pages
Proc. SPIE 1806, Optical Computing, (12 July 1993); doi: 10.1117/12.147840
Show Author Affiliations
Ichiro Tohyama, Univ. of Tsukuba (Japan)
Yoshio Hayasaki, Univ. of Tsukuba (Japan)
Toyohiko Yatagai, Univ. of Tsukuba (Japan)
Yoshio Hayasaki, Univ. of Tsukuba (Japan)
Toyohiko Yatagai, Univ. of Tsukuba (Japan)
Published in SPIE Proceedings Vol. 1806:
Optical Computing
Andrey M. Goncharenko; Fedor V. Karpushko; George V. Sinitsyn; Sergey P. Apanasevich, Editor(s)
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