Enhancing Fault Tolerance of Radial Basis Functions

Eickhoff R, Rückert U (2006)
In: Neural Networks, 2006. IJCNN '06. International Joint Conference on. 5066-5073.

Konferenzbeitrag | Veröffentlicht| Englisch
 
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Autor/in
Eickhoff, R.; Rückert, UlrichUniBi
Abstract / Bemerkung
The challenge of future nanoelectronic applications, e.g. in quantum computing or in molecular computing, is to assure reliable computation facing a growing number of malfunctioning and failing computational units. Modeled on biology artificial neural networks are intended to be one preferred architecture for these applications because their architectures allow distributed information processing and, therefore, will result in tolerance to malfunctioning neurons and in robustness to noise. In this work, methods to enhance fault tolerance to permanently failing neurons of Radial Basis Function networks are investigated for function approximation applications. Therefore, a relevance measure is introduced which can be used to enhance the fault tolerance or, on the contrary, to control the network complexity if it is used for pruning.
Stichworte
distributed information processing; function approximation application; radial basis function networks; biology artificial neural networks; fault tolerance enhancement; radial basis function networks; function approximation; fault tolerance
Erscheinungsjahr
2006
Titel des Konferenzbandes
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Seite(n)
5066-5073
Page URI
https://pub.uni-bielefeld.de/record/2286083

Zitieren

Eickhoff R, Rückert U. Enhancing Fault Tolerance of Radial Basis Functions. In: Neural Networks, 2006. IJCNN '06. International Joint Conference on. 2006: 5066-5073.
Eickhoff, R., & Rückert, U. (2006). Enhancing Fault Tolerance of Radial Basis Functions. Neural Networks, 2006. IJCNN '06. International Joint Conference on, 5066-5073. doi:10.1109/IJCNN.2006.247234
Eickhoff, R., and Rückert, U. (2006). “Enhancing Fault Tolerance of Radial Basis Functions” in Neural Networks, 2006. IJCNN '06. International Joint Conference on 5066-5073.
Eickhoff, R., & Rückert, U., 2006. Enhancing Fault Tolerance of Radial Basis Functions. In Neural Networks, 2006. IJCNN '06. International Joint Conference on. pp. 5066-5073.
R. Eickhoff and U. Rückert, “Enhancing Fault Tolerance of Radial Basis Functions”, Neural Networks, 2006. IJCNN '06. International Joint Conference on, 2006, pp.5066-5073.
Eickhoff, R., Rückert, U.: Enhancing Fault Tolerance of Radial Basis Functions. Neural Networks, 2006. IJCNN '06. International Joint Conference on. p. 5066-5073. (2006).
Eickhoff, R., and Rückert, Ulrich. “Enhancing Fault Tolerance of Radial Basis Functions”. Neural Networks, 2006. IJCNN '06. International Joint Conference on. 2006. 5066-5073.

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