Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline

Intelligent real-world systems critically depend on expressive information about their system state and changing operation conditions, e.g., due to variation in temperature, location, wear, or aging. To provide this information, online inference and learning attempts to perform state estimation and...

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Hauptverfasser:	Ewering, Jan-Hendrik, Volkmann, Björn, Ehlers, Simon F. G, Seel, Thomas, Meindl, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Systems and Control
Online-Zugang:	Volltext bestellen
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