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Online learning of neural state-space models

Györök, Bendegúz et al.
arXiv (All) · Papers
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machine-learningsystems-and-control
Recent advances in deep-learning-based nonlinear system identification have led to encoder-based estimation of neural state-space (ANN-SS) models that achieve state-of-the-art performance in offline settings by estimating initial model states from past input-output data. These methods are typically
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