Holography in artificial neural networks

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 learni...

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Veröffentlicht in:	Nature (London) 1990-01, Vol.343 (6256), p.325-330
Hauptverfasser:	Psaltis, Demetri, Brady, David, Gu, Xiang-Guang, Lin, Steven
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Algorithms Applied sciences Artificial neural networks Brain - physiology Brain research Computer Simulation Computers Crystals Design Digital computers Electric, optical and optoelectronic circuits Electronics Exact sciences and technology Fractals Holography Humanities and Social Sciences Lasers Learning - physiology Light Mathematics multidisciplinary Nervous system Neural networks Neural Pathways - physiology Neural Pathways - ultrastructure Neurons Neurons - physiology Neurons - ultrastructure Neurosciences Photography Physics Reconstruction review-article Science Science (multidisciplinary) Semiconductors Software Synapses - physiology
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Beschreibung
Zusammenfassung:	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.
ISSN:	0028-0836 1476-4687
DOI:	10.1038/343325a0