Reconfigurable Integrated Photonic Unitary Neural Networks With Phase Encoding Enabled by In-Situ Training
Photonic neural networks are emerging as promising computing platforms for artificial intelligence (AI). Particularly, integrated photonic unitary neural networks (IPUNNs) are capable of mitigating gradient vanishing/explosion problems when deeper neural networks are constructed. Furthermore, their...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10663838/ |
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