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Reservoir Computing Using Laser Networks
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DOI：10.1109/JSTQE.2019.2927578.png)
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Reservoir computing is a neuromorphic computing scheme inspired by the human brain. It has found great success as a versatile hardware-compatible application of machine learning concepts. In this paper, we highlight the fundamental working principles and important characteristics of reservoir computing with a particular focus on photonic systems and networks. These systems can further be enhanced by the inclusion of delayed variables to produce complex spatiotemporally mixed time-multiplexed networks. We use a simple nonlinear oscillator model, that is not only applicable to lasers, hut can also describe a variety of other oscillating systems.
Keyword:
Networks
reservoir computing
time delay
laser dynamics
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