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Roadmap on Material-Function Mapping for Photonic-Electronic Hybrid Neural Networks
[article]
2019
arXiv
pre-print
Driven by machine-learning tasks neural networks have demonstrated useful capabilities as nonlinear hypothesis classifiers. The underlying technologies performing the dot product multiplication, the summation, and the nonlinear thresholding on the input data in electronics, however, are limited by the same capacitive challenges known from electronic integrated circuits. The optical domain, in contrast, provides low delay interconnectivity suitable for such node distributed non Von Neumann
arXiv:1905.06371v2
fatcat:bxdzjltafvatbcogmw7zet54lq