The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks
Open accessAbstract
We introduce an electro-optic hardware platform for nonlinear activation functions in optical neural networks. The optical-to-optical nonlinearity operates by converting a small portion of the input optical signal into an analog electric signal, which is used to intensity -modulate the original optical signal with no reduction in processing speed. Our scheme allows for complete nonlinear on-off contrast in transmission at relatively low optical power thresholds and eliminates the requirement of having additional optical sources between each of the layers of the network Moreover, the activation function is reconfigurable via electrical bias, allowing it to be programmed or trained to synthesize a variety of nonlinear responses. Using numerical simulations, we demonstrate that this activation function significantly improves the expressiveness of optical neural networks, allowing them to perform well on two benchmark machine learning tasks: learning a multi-input exclusive-OR (XOR) logic function and classification of images of handwritten numbers from the MNIST dataset. The addition of the nonlinear activation function improves test accuracy on the MNIST task from 85% to 94%.
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Cites
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Photonics for artificial intelligence and neuromorphic computing
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An optical neural chip for implementing complex-valued neural network
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Experimentally realized in situ backpropagation for deep learning in photonic neural networks
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Self-citationSingle chip photonic deep neural network with accelerated training
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Programmable surface plasmonic neural networks for microwave detection and processing
Gao, X., Ma, Q., Gu, Z., Cui, W. Y., Liu, C., Zhang, J., & Cui, T. J. (2023) · Nature Electronics · doi:10.1038/s41928-023-00951-x · Cited by 106
Metadata
- Authors
- Williamson, I. A. D., Hughes, T. W., Minkov, M., Bartlett, B., Pai, S., & Fan, S.
- Venue
- IEEE Journal of Selected Topics in Quantum Electronics
- Published
- 2020-01
- Volume
- 26
- Issue
- 1
- Pages
- 1-12
- ISSN
- 1077-260X (ISSN-L)
- 1558-4542
- OpenAlex
- W2964082513
- Cited by
- 346
- References
- 32
- FWCI
- 14.97
- Type
- journal article
- Language
- en
- Open access
- green
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