Neurally imprinted stable vector fields

Lemme A, Neumann K, Reinhart F, Steil JJ (2013)
Presented at the European Symposium on Artificial Neural Networks, (best paper award).

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
We present a novel learning scheme to imprint stable vector fields into Extreme Learning Machines (ELMs). The networks represent movements, where asymptotic stability is incorporated through constraints derived from Lyapunov stability theory. We show that our approach successfully performs stable and smooth point-to-point movements learned from human handwriting movements.
Stichworte
CoR-Lab Publication
Erscheinungsjahr
2013
Seite(n)
327-332
Konferenz
European Symposium on Artificial Neural Networks
Konferenzort
(best paper award)
Page URI
https://pub.uni-bielefeld.de/record/2581205

Zitieren

Lemme A, Neumann K, Reinhart F, Steil JJ. Neurally imprinted stable vector fields. Presented at the European Symposium on Artificial Neural Networks, (best paper award).
Lemme, A., Neumann, K., Reinhart, F., & Steil, J. J. (2013). Neurally imprinted stable vector fields. Presented at the European Symposium on Artificial Neural Networks, (best paper award).
Lemme, A., Neumann, K., Reinhart, F., and Steil, J. J. (2013).“Neurally imprinted stable vector fields”. Presented at the European Symposium on Artificial Neural Networks, (best paper award).
Lemme, A., et al., 2013. Neurally imprinted stable vector fields. Presented at the European Symposium on Artificial Neural Networks, (best paper award).
A. Lemme, et al., “Neurally imprinted stable vector fields”, Presented at the European Symposium on Artificial Neural Networks, (best paper award), 2013.
Lemme, A., Neumann, K., Reinhart, F., Steil, J.J.: Neurally imprinted stable vector fields. Presented at the European Symposium on Artificial Neural Networks, (best paper award) (2013).
Lemme, Andre, Neumann, Klaus, Reinhart, Felix, and Steil, Jochen J. “Neurally imprinted stable vector fields”. Presented at the European Symposium on Artificial Neural Networks, (best paper award), 2013.
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2019-09-06T09:18:13Z
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