While process variations are becoming more significant with each new IC technology generation, they are often modeled via linear regression models so that the resulting performanc...
Xin Li, Jiayong Le, Padmini Gopalakrishnan, Lawren...
Abstract-- This paper describes the stochastic model order reduction algorithm via stochastic Hermite Polynomials from the practical implementation perspective. Comparing with exis...
Yi Zou, Yici Cai, Qiang Zhou, Xianlong Hong, Sheld...
9, IO]. However, unlike the case with static timing, it is not so easy We show how recent advances in the handling of correlated interval representations of range uncertainty can b...
— Statistical static timing analysis deals with the increasing variations in manufacturing processes to reduce the pessimism in the worst case timing analysis. Because of the cor...
Bing Li, Ning Chen, Manuel Schmidt, Walter Schneid...
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...