Robustness of Radial Basis Functions
Eickhoff R, Rückert U (2005)
In: Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN). Cabestany J, Prieto A, Sandoval DF (Eds); (3512). Barcelona, Spain: 264-271.
Konferenzbeitrag
| Veröffentlicht | Englisch
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Autor*in
Eickhoff, Ralf;
Rückert, UlrichUniBi
Herausgeber*in
Cabestany, J.;
Prieto, A.;
Sandoval, D.F.
Abstract / Bemerkung
Neural networks are intended to be used in future nanoelectronic technology since these architectures seem to be robust to malfunctioning elements and noise in its inputs and parameters. In this work, the robustness of radial basis function networks is analyzed in order to operate in noisy and unreliable environment. Furthermore, upper bounds on the mean square error under noise contaminated parameters and inputs are determined if the network parameters are constrained. To achieve robuster neural network architectures fundamental methods are introduced to identify sensitive parameters and neurons.
Erscheinungsjahr
2005
Titel des Konferenzbandes
Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN)
Ausgabe
3512
Seite(n)
264-271
Page URI
https://pub.uni-bielefeld.de/record/2288806
Zitieren
Eickhoff R, Rückert U. Robustness of Radial Basis Functions. In: Cabestany J, Prieto A, Sandoval DF, eds. Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN). Barcelona, Spain; 2005: 264-271.
Eickhoff, R., & Rückert, U. (2005). Robustness of Radial Basis Functions. In J. Cabestany, A. Prieto, & D. F. Sandoval (Eds.), Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN) (pp. 264-271). Barcelona, Spain.
Eickhoff, Ralf, and Rückert, Ulrich. 2005. “Robustness of Radial Basis Functions”. In Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN), ed. J. Cabestany, A. Prieto, and D.F. Sandoval, 264-271. Barcelona, Spain.
Eickhoff, R., and Rückert, U. (2005). “Robustness of Radial Basis Functions” in Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN), Cabestany, J., Prieto, A., and Sandoval, D. F. eds. (Barcelona, Spain), 264-271.
Eickhoff, R., & Rückert, U., 2005. Robustness of Radial Basis Functions. In J. Cabestany, A. Prieto, & D. F. Sandoval, eds. Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN). Barcelona, Spain, pp. 264-271.
R. Eickhoff and U. Rückert, “Robustness of Radial Basis Functions”, Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN), J. Cabestany, A. Prieto, and D.F. Sandoval, eds., Barcelona, Spain: 2005, pp.264-271.
Eickhoff, R., Rückert, U.: Robustness of Radial Basis Functions. In: Cabestany, J., Prieto, A., and Sandoval, D.F. (eds.) Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN). p. 264-271. Barcelona, Spain (2005).
Eickhoff, Ralf, and Rückert, Ulrich. “Robustness of Radial Basis Functions”. Proceedings of the 8th International Work-Conference on Artificial Neural Networks (IWANN). Ed. J. Cabestany, A. Prieto, and D.F. Sandoval. Barcelona, Spain, 2005. 264-271.
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