Holography in artificial neural networks.
Publication
, Journal Article
Psaltis, D; Brady, D; Gu, XG; Lin, S
Published in: Nature
January 1990
The dense interconnections that characterize neural networks are most readily implemented using optical signal processing. Optoelectronic 'neurons' fabricated from semiconducting materials can be connected by holographic images recorded in photorefractive crystals. Processes such as learning can be demonstrated using holographic optical neural networks.
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Published In
Nature
DOI
EISSN
1476-4687
ISSN
0028-0836
Publication Date
January 1990
Volume
343
Issue
6256
Start / End Page
325 / 330
Related Subject Headings
- Synapses
- Semiconductors
- Neurons
- Neural Pathways
- Mathematics
- Learning
- Holography
- General Science & Technology
- Computers
- Computer Simulation
Citation
APA
Chicago
ICMJE
MLA
NLM
Psaltis, D., Brady, D., Gu, X. G., & Lin, S. (1990). Holography in artificial neural networks. Nature, 343(6256), 325–330. https://doi.org/10.1038/343325a0
Psaltis, D., D. Brady, X. G. Gu, and S. Lin. “Holography in artificial neural networks.” Nature 343, no. 6256 (January 1990): 325–30. https://doi.org/10.1038/343325a0.
Psaltis D, Brady D, Gu XG, Lin S. Holography in artificial neural networks. Nature. 1990 Jan;343(6256):325–30.
Psaltis, D., et al. “Holography in artificial neural networks.” Nature, vol. 343, no. 6256, Jan. 1990, pp. 325–30. Epmc, doi:10.1038/343325a0.
Psaltis D, Brady D, Gu XG, Lin S. Holography in artificial neural networks. Nature. 1990 Jan;343(6256):325–330.
Published In
Nature
DOI
EISSN
1476-4687
ISSN
0028-0836
Publication Date
January 1990
Volume
343
Issue
6256
Start / End Page
325 / 330
Related Subject Headings
- Synapses
- Semiconductors
- Neurons
- Neural Pathways
- Mathematics
- Learning
- Holography
- General Science & Technology
- Computers
- Computer Simulation