Web: http://arxiv.org/abs/2201.08660

Jan. 24, 2022, 2:10 a.m. | Marco Forgione, Aneri Muni, Dario Piga, Marco Gallieri

cs.LG updates on arXiv.org arxiv.org

This paper presents a transfer learning approach which enables fast and
efficient adaptation of Recurrent Neural Network (RNN) models of dynamical
systems. A nominal RNN model is first identified using available measurements.
The system dynamics are then assumed to change, leading to an unacceptable
degradation of the nominal model performance on the perturbed system. To cope
with the mismatch, the model is augmented with an additive correction term
trained on fresh data from the new dynamic regime. The correction term …

arxiv identification networks neural neural networks

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