Abstract

We proposed a 32-channel 50G AWG as the core device to implement the on-chip optical reservoir computing. With appropriate iterative mode and output-level training strategy, the chip has achieved good results in predicting Macky-Glass series. For sequences of 1000 length, this type of optical reservoir calculation can obtain an absolute error of about 0.02 and a relative error of 0.018.

Keywords:
Computer science Grating Waveguide Chip Reservoir computing Series (stratigraphy) Arrayed waveguide grating Core (optical fiber) Approximation error Optics Channel (broadcasting) Mode (computer interface) Algorithm Physics Wavelength-division multiplexing Telecommunications Geology Artificial intelligence

Metrics

6
Cited By
1.53
FWCI (Field Weighted Citation Impact)
5
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Neural Networks and Reservoir Computing
Physical Sciences →  Computer Science →  Artificial Intelligence
Optical Network Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Photonic and Optical Devices
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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