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Learning approaches in motion control using neural networks

Sanchez, A. (1993) Learning approaches in motion control using neural networks. In: Proc. IEEE Asia-Pacific Workshop in Motion Control, Singapore, July 15-16, 1993.

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Abstract

In this paper a selection of supervised learning approaches in motion control using neural networks is presented. This includes backpropagation, radial basis functions, second-order methods, and wavelets. Emphasis is given to their functional representation and optimization techniques used with reference of their use in motion control.

Item URL in elib:https://elib.dlr.de/28054/
Document Type:Conference or Workshop Item (Paper)
Additional Information: LIDO-Berichtsjahr=1993, pages=6,
Title:Learning approaches in motion control using neural networks
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sanchez, A.UNSPECIFIEDUNSPECIFIED
Date:1993
Journal or Publication Title:Proc. IEEE Asia-Pacific Workshop in Motion Control, Singapore, July 15-16, 1993
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Learning, motion control, neurocomputing, neural networks
HGF - Research field:UNSPECIFIED
HGF - Program:Space (old)
HGF - Program Themes:W SY - Technik für Raumfahrtsysteme
DLR - Research area:UNSPECIFIED
DLR - Program:W SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):UNSPECIFIED
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (until 2012) > Institut für Dynamik der Flugsysteme
Deposited By: DLR-Beauftragter, elib
Deposited On:02 Apr 2006
Last Modified:27 Apr 2009 06:52

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