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A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data
Recent research has established the effectiveness of machine learning for data-driven prediction of the future evolution of unknown dynamical systems, including chaotic systems.
Model-Free Control of Dynamical Systems with Deep Reservoir Computing
We propose and demonstrate a nonlinear control method that can be applied to unknown, complex systems where the controller is based on a type of artificial neural network known as a reservoir computer.
Rapid Time Series Prediction with a Hardware-Based Reservoir Computer
Reservoir computing is a neural network approach for processing time-dependent signals that has seen rapid development in recent years.
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