NDLI: Practical Implementation of Stochastic Parameterized Model Order Reduction via Hermite Polynomial Chaos

Content Provider	IEEE Xplore Digital Library
Author	Yi Zou Yici Cai Qiang Zhou Xianlong Hong Tan, S.X.-D. Le Kang
Copyright Year	2007
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing (Yi Zou)
Abstract	This paper describes the stochastic model order reduction algorithm via stochastic Hermite polynomials from the practical implementation perspective. Comparing with existing work on stochastic interconnect analysis and parameterized model order reduction, we generalized the input variation representation using polynomial chaos (PC) to allow for accurate modeling of non-Gaussian input variations. We also explore the implicit system representation using sub-matrices and improved the efficiency for solving the linear equations utilizing block matrix structure of the augmented system. Experiments show that our algorithm matches with Monte Carlo methods very well while keeping the algorithm effective. And the PC representation of non-Gaussian variables gains more accuracy than Taylor representation used in previous work (Wang et al., 2004).
Starting Page	367
Ending Page	372
File Size	560724
Page Count	6
File Format	PDF
ISBN	1424406293
DOI	10.1109/ASPDAC.2007.358013
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-01-23
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Polynomials Chaos Integrated circuit interconnections Equations Stochastic systems Analytical models Circuit simulation Taylor series System performance
Content Type	Text
Resource Type	Article

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