Abstract
The design process of integrated circuits (IC) aims at a high yield as well as a good IC-performance. The distribution of measured output variables will not be standard Gaussian anymore. In fact, the corresponding probability density function has a more flat shape than in case of standard Gaussian. In order to optimize the yield one needs a statistical model for the observed distribution. One of the promising approaches is to use the so-called Generalized Gaussian distribution function and to estimate its defining parameters. We propose a numerical fast and reliable method for computing these parameters.
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Acknowledgements
The authors acknowledge support from the projects CORTIF (http://cortif.xlim.fr/): Coexistence Of Radiofrequency Transmission In the Future, a CATRENE project (Cluster for Application and Technology Research in Europe on NanoElectronics, http://www.catrene.org/) and nanoCOPS (http://fp7-nanocops.eu/): Nanoelectronic COupled Problems Solutions, FP7-ICT-2013-11/619166.
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Beelen, T.G.J., Dohmen, J.J., ter Maten, E.J.W., Tasić, B. (2018). Fitting Generalized Gaussian Distributions for Process Capability Index. In: Langer, U., Amrhein, W., Zulehner, W. (eds) Scientific Computing in Electrical Engineering. Mathematics in Industry(), vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-75538-0_16
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DOI: https://doi.org/10.1007/978-3-319-75538-0_16
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