Bibliograph. Daten | Oubbati, Mohamed; Levi, Paul; Schanz, Michael: Meta-learning for Adaptive Identification of Non-linear Dynamical Systems.. In: Proceedings of the Joint 20th IEEE International Symposium on Intelligent Control & 13th Mediterranean Conference on Control and Automation (2005 ISIC-MED).. Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik. S. 473-478, englisch. Limassol, Cyprus: IEEE, 27. Juni 2005. Artikel in Tagungsband (Konferenz-Beitrag).
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Körperschaft | IEEE |
CR-Klassif. | I.2.8 (Problem Solving, Control Methods, and Search)
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Keywords | Adaptive Identification; RNNs; Non-linear Dynamical Systems; Meta-learning. |
Kurzfassung | Adaptive Identification of Non-linear Dynamical Systems via Recurrent Neural Networks (RNNs) is presented in this paper. We explore the notion that a fixed-weight RNN needs to change only its internal state to change its behavior policy. This ability is acquired through prior training procedure that enable the learning of adaptive behaviors. Some simulation results are presented.
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Kontakt | Mohamed.Oubbati@informatik.uni-stuttgart.de |
Abteilung(en) | Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Bildverstehen
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Projekt(e) | SFB-627
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Eingabedatum | 30. Juli 2005 |
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