Journal
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
Volume 26, Issue 1, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTQE.2019.2936281
Keywords
Optical Computing; Reservoir Computing; Optical neural networks; Light scattering; Chaotic time series; Network quantization
Categories
Funding
- Defense Advanced Research Projects Agency (DARPA) [HR00111890042]
- H2020 European Research Council (ERC) [724473]
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Reservoir Computing is a relatively recent computational framework based on a large Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir Computing have been proposed to improve speed and energy efficiency. In this study, we report new advances in Optical Reservoir Computing using multiple light scattering to accelerate the recursive computation of the reservoir states. Two different spatial light modulation technologies, namely, phase or binary amplitude modulations, are compared. Phase modulation is a promising direction already employed in other photonic implementations of Reservoir Computing. Additionally, we report a Digital-Micromirror-based Reservoir Computing at up to 640 Hz, more than double the previously reported frequency using a remotely controlled optical device developed by LightOn, and present new binarization strategies to improve the performance of binarized Reservoir Computing.
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