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» Stochastic Model of Stroke Order Variation
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GLVLSI
2008
IEEE
129views VLSI» more  GLVLSI 2008»
14 years 2 months ago
Variational capacitance modeling using orthogonal polynomial method
In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spect...
Jian Cui, Gengsheng Chen, Ruijing Shen, Sheldon X....
ICCD
2006
IEEE
157views Hardware» more  ICCD 2006»
14 years 4 months ago
Statistical Analysis of Power Grid Networks Considering Lognormal Leakage Current Variations with Spatial Correlation
— As the technology scales into 90nm and below, process-induced variations become more pronounced. In this paper, we propose an efficient stochastic method for analyzing the vol...
Ning Mi, Jeffrey Fan, Sheldon X.-D. Tan
ASPDAC
2009
ACM
161views Hardware» more  ASPDAC 2009»
14 years 2 months ago
Risk aversion min-period retiming under process variations
— Recent advances in statistical timing analysis (SSTA) achieve great success in computing arrival times under variations by extending sum and maximum operations to random variab...
Jia Wang, Hai Zhou
DATE
2007
IEEE
92views Hardware» more  DATE 2007»
14 years 1 months ago
Random sampling of moment graph: a stochastic Krylov-reduction algorithm
In this paper we introduce a new algorithm for model order reduction in the presence of parameter or process variation. Our analysis is performed using a graph interpretation of t...
Zhenhai Zhu, Joel R. Phillips
NIPS
2008
13 years 9 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong