Big-Data Tensor Recovery for High-Dimensional Uncertainty Quantification of Process Variations
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DOI: 10.1109/tcpmt.2016.2628703
Abstract: Fabrication process variations are a major source of yield degradation in the nanoscale design of integrated circuits (ICs), microelectromechanical systems (MEMSs), and photonic circuits. Stochastic spectral methods are a promising technique to quantify the uncertainties… read more here.
Keywords: big data; high dimensional; process variations; uncertainty quantification ... See more keywords