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Carsten Peterson
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Optoelectronic implementation of multilayer neural networks in a single photorefractive crystal
Author
Summary, in English
We present a novel, versatile optoelectronic neural network architecture for implementing supervised learning algorithms in photorefractive materials. The system is based on spatial multiplexing rather than the more commonly used angular multiplexing of the interconnect gratings. This simple, single-crystal architecture implements a variety of multilayer supervised learning algorithms including mean field theory, back-propagation, and Marr-Albus-Kanerva style algorithms. Extensive simulations show how beam depletion, rescattering, absorption, and decay effects of the crystal are compensated for by suitably modified supervised learning algorithms.
Department/s
- Computational Biology and Biological Physics - Has been reorganised
Publishing year
1990-04-01
Language
English
Pages
359-368
Publication/Series
Optical Engineering
Volume
29
Issue
4
Document type
Journal article
Publisher
SPIE
Topic
- Computer Science
Status
Published
ISBN/ISSN/Other
- ISSN: 0091-3286