A linear optical reservoir with photodetector nonlinearity improves task performance and attractor reconstruction by using transient coupling and delayed feedback to access multi-step integration schemes that compensate for missing higher-order terms, at the cost of more virtual nodes.
Machine learning based on reservoir computing with time-delayed optoelectronic and pho- tonic systems.Chaos: An Interdisciplinary Journal of Nonlinear Science, 30(1), 2020
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Understanding Task Performance of Time-Multiplexed Optical Reservoir Computing via Polynomial Expansion
A linear optical reservoir with photodetector nonlinearity improves task performance and attractor reconstruction by using transient coupling and delayed feedback to access multi-step integration schemes that compensate for missing higher-order terms, at the cost of more virtual nodes.