1 April 1990 Optoelectronic implementation of multilayer neural networks in a single photorefractive crystal
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Optical Engineering, 29(4), (1990). doi:10.1117/12.55604
Abstract
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, backpropagation, 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.
Carsten Peterson, Stephen R. Redfield, James D. Keeler, Eric Hartman, "Optoelectronic implementation of multilayer neural networks in a single photorefractive crystal," Optical Engineering 29(4), (1 April 1990). http://dx.doi.org/10.1117/12.55604
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KEYWORDS
Crystals

Neural networks

Machine learning

Multiplexing

Neurons

Laser crystals

Spatial light modulators

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