FTSET-a software tool for fault tolerance evaluation and improvement
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-009-0329-0.pdf
Reference16 articles.
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3. Eickhoff R, Rückert U (2005) Tolerance of radial basis functions against stuck-at-faults. In: International conference of artificial neural networks, Poland, pp 1003–1008
4. Phatak DS (1995) Complete and partial fault tolerance of feedforward neural nets. IEEE Trans Neural Netw 6(2):446–456
5. Tchernev EB, Phatak DS (2005) Investigating the fault tolerance of neural networks, NCA
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