Pareto-optimal noise and approximation properties of RBFnetworks

Eickhoff R, Rückert U (2006)
In: Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). Athens, Greece: pp.:993-1002.

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Neural networks are intended to be robust to noise and tolerant to failures in their architecture. Therefore, these systems are particularly interesting to be integrated in hardware and to be operating under noisy environment. In this work, measurements are introduced which can decrease the sensitivity of Radial Basis Function networks to noise without any degradation in their approximation capability. For this purpose, pareto-optimal solutions are determined for the parameters of the network.
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Eickhoff R, Rückert U. Pareto-optimal noise and approximation properties of RBFnetworks. In: Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). Athens, Greece; 2006: pp.:993-1002.
Eickhoff, R., & Rückert, U. (2006). Pareto-optimal noise and approximation properties of RBFnetworks. Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN), pp.:993-1002.
Eickhoff, R., and Rückert, U. (2006). “Pareto-optimal noise and approximation properties of RBFnetworks” in Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN) (Athens, Greece), pp.:993-1002.
Eickhoff, R., & Rückert, U., 2006. Pareto-optimal noise and approximation properties of RBFnetworks. In Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). Athens, Greece, pp. pp.:993-1002.
R. Eickhoff and U. Rückert, “Pareto-optimal noise and approximation properties of RBFnetworks”, Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN), Athens, Greece: 2006, pp.pp.:993-1002.
Eickhoff, R., Rückert, U.: Pareto-optimal noise and approximation properties of RBFnetworks. Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). p. pp.:993-1002. Athens, Greece (2006).
Eickhoff, Ralf, and Rückert, Ulrich. “Pareto-optimal noise and approximation properties of RBFnetworks”. Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN). Athens, Greece, 2006. pp.:993-1002.
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