22 March 1999 Neural-based production yield prediction: an RBF-based approach
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Prediction and modeling in the case of non linear systems (or processes), especially of complex industrial processes are known being a class of involved problems. In this paper, we deal with the production yield prediction dilemma in VLSI manufacturing. An RBF neural networks based approach and its hardware implementation on a ZISC neural board have been presented. Experimental results comparing our approach with an expert have been reported and discussed.
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Kurosh Madani, Ghislain de Tremiolles, Erin Williams, Pascal Tannhof, "Neural-based production yield prediction: an RBF-based approach", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); doi: 10.1117/12.342904; https://doi.org/10.1117/12.342904

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