Optical neural networks

Classical optical information processing and classical neural networks can be adapted and combined to create optical neural networks which offer significant and fundamental advantages over electronic neural networks in various well-defined cases. A systematic morphology of optical neural networks is...

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Bibliographic Details
Published in:Proceedings of the IEEE 1989-10, Vol.77 (10), p.1573-1583
Main Authors: Caulfield, H.J., Kinser, J., Rogers, S.K.
Format: Article
Language:English
Subjects:
426000 - Engineering- Components, Electron Devices & Circuits- (1990-)
990200 - Mathematics & Computers
ANIMAL CELLS
Applied sciences
Biological information theory
Biological neural networks
Biology computing
Biomedical optical imaging
Circuit properties
COMPUTER NETWORKS
COMPUTERS
DIGITAL COMPUTERS
Electric, optical and optoelectronic circuits
ELECTRO-OPTICAL EFFECTS
ELECTRONIC CIRCUITS
Electronics
ENGINEERING
Exact sciences and technology
GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
IMAGE PROCESSING
Information processing
LEARNING
Military computing
Miscellaneous
NERVE CELLS
Neural networks
Neurons
Optical computing
Optical fiber networks
OPTICAL SYSTEMS
PARALLEL PROCESSING
PROCESSING
PROGRAMMING
SIMULATION
SOMATIC CELLS
SUPERCOMPUTERS
USES
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Description
Summary:Classical optical information processing and classical neural networks can be adapted and combined to create optical neural networks which offer significant and fundamental advantages over electronic neural networks in various well-defined cases. A systematic morphology of optical neural networks is presented. Special problems they create are discussed. The state of the art of their implementation is indicated, and some supportable speculations on their future are given.< >
ISSN:0018-9219
1558-2256
DOI:10.1109/5.40669