Dr.-Ing. Michael Vogt

Aufgabenbereich

Support Vector Machines for Identification and Classification Problems in Control Engineering

Kontakt

Vogt, Michael (2013):
System identification techniques based on support vector machines without bias term.
In: International Journal of Adaptive Control and Signal Processing, 27 (9), S. 809-826. Wiley & Sons Ltd., e-ISSN 10991115,
DOI: 10.1002/acs.2404,
[Artikel]

Vogt, Michael (2008):
Support Vector Machines for Identification and Classification Problems in Control Engineering.
In: VDI Fortschrittsberichte, 8, Düsseldorf, VDI-Verlag, TU Darmstadt, ISBN 978-3-18-513808-9,
[Dissertation]

Vogt, Michael ; Moissl, Ulrich ; Schaab, Jochen (2006):
Heart Rate Classification Using Support Vector Machines.
In: From Data and Information Analysis to Knowledge Engineering : Proceedings of the 29th Annual Conference of The Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005. With ... 120 tables / Myra Spiliopoulou ... (eds)., S. 716-723, Berlin ; Heidelberg [u.a.], Springer, ISBN 978-3-540-31313-7,
[Buchkapitel]

Schaab, Jochen ; Münchhof, Marco ; Vogt, Michael ; Isermann, Rolf (2005):
Identification of a Hydraulic Servo-Axis Using Support Vector Machines.
In: IFAC Proceedings Volumes, 38 (1), S. 722-727. Elsevier ScienceDirect, ISSN 1474-6670,
DOI: 10.3182/20050703-6-CZ-1902.00121,
[Artikel]

Fink, Alexander ; Zimmerschied, Ralf ; Vogt, Michael ; Isermann, Rolf (2005):
Nonlinear System Identification with Local Linear Neuro-Fuzzy Models.
In: IEE control engineering series, 2005, In: Intelligent Control Systems Using Computational Intelligence Techniques / ed. by A. E. Ruano, S. 153-175, London, Institution of Electrical Engineers, ISBN 0-86341-489-3,
[Buchkapitel]

Kecman, Voijslav ; Huang, Te-Ming ; Vogt, Michael
Wang, Lipo (Hrsg.) (2005):
Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance.
In: Studies in Fuzziness and Soft Computing, 2005, In: Support Vector Machines : Theory and Applications, S. 255-274, Berlin [u.a.], Springer, ISBN 3-540-24388-7,
[Buchkapitel]

Vogt, Michael ; Kecman, V. (2005):
An Active-Set Algorithm for Support Vector Machines in Nonlinear System Identification.
In: Nonlinear control systems 2004 : (NOLCOS 2004) ; a proceedings volume from the 6th IFAC symposium, Stuttgart, Germany, 1 - 3 September 2004 / ed. by F. Allgöwer, Kidlington, Oxford, Elsevier, 6th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2004), Stuttgart, September 1-3, [Konferenzveröffentlichung]

Vogt, Michael ; Kecman, Voijslav
Wang, Lipo (Hrsg.) (2005):
Active-Set Methods for Support Vector Machines.
In: Studies in Fuzziness and Soft Computing, 2005, In: Support Vector Machines : Theory and Applications, S. 133-158, Berlin [u.a.], Springer, ISBN 3-540-24388-7,
[Buchkapitel]

Vogt, Michael ; Müller, Norbert ; Isermann, Rolf (2004):
On-line Adaptation of Grid-Based Look-Up Tables Using a Fast Linear Regression Technique.
In: Journal of Dynamic Systems, Measurement and Control, 126 (4), S. 732-739. American Society of Mechanical Engineers, ISSN 0022-0434,
DOI: 10.1115/1.1849241,
[Artikel]

Vogt, Michael ; Spreitzer, Karsten ; Kecman, V. (2004):
Identification of a High Efficiency Boiler by Support Vector Machines without Bias Term.
In: SYSID, Symposium on System Identification: System identification ... proceedings / ed. by Paul M.J. van den Hof ...- Oxford: Elsevier, ISBN 0-08-043709-5, Oxford, Elsevier, 13th IFAC Symposium on System Identification (SYSID 2003), Rotterdam, Niederlande, 27.-29. August, [Konferenzveröffentlichung]

Vogt, Michael ; Spreitzer, K. ; Kecman, V. (2003):
Identification of a high efficiency boiler by support vector machines without bias term.
In: IFAC Proceedings Volumes, 36 (16), S. 465-470. Elsevier ScienceDirect, ISSN 14746670,
DOI: 10.1016/S1474-6670(17)34805-X,
[Artikel]

Kecman, V. ; Vogt, Michael ; Huang, T. M. (2003):
On the Equality of Kernel AdaTron and Sequential Minimal Optimization in Classification and Regression Tasks and Alike Algorithms for Kernel Machines.
In: ESAAN, European Symposium on Artificial Neural Networks <11, 2003, Brügge>: Proceedings, 11th European Symposium on Artificial Neural Networks (ESANN 2003), Bruges, Belgium, April 22-25, [Konferenzveröffentlichung]

Vogt, Michael
Technische Universität Darmstadt (Urheber) (2002):
SMO Algorithms for Support Vector Machines without Bias Term.
[Report]

Wolfram, A. ; Vogt, Michael (2002):
Zeitdiskrete Filteralgorithmen zur Erzeugung zeitlicher Ableitungen (Discrete-Time Filter Algorithms for the Computation of Time-Derivatives).
In: at - Automatisierungstechnik, 50 (7_2002), S. 346-353. ISSN 0178-2312,
[Artikel]

Moseler, Olaf ; Vogt, Michael (2000):
FIT - Filtering and Identification Tool.
In: SYSID 2000: Proceedings of the 12th IFAC Symposium on Identification Systems, Elsevier, Amsterdam (u.a.), Elsevier, 12th IFAC Symposium on System Identification (SYSID 2000), Santa Barbara, CA, USA, 21.-23. Juni, [Konferenzveröffentlichung]