Efficient Time-Domain Variability Analysis using Parameterized Model-Order Reduction

被引：0
|
作者：
Tao, Ye [1 ]
Nouri, Behzad [1 ]
Nakhla, Michel [1 ]
Achar, Ramachandra [1 ]
机构：
[1] Carleton Univ, Dept Elect, Ottawa, ON K1S 5B6, Canada
来源：
2016 IEEE 20TH WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI) | 2016年
关键词：
DECOUPLED POLYNOMIAL CHAOS; INTERCONNECTS; SYSTEMS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A fast algorithm is presented for time-domain statistical analysis of large circuits with multiple stochastic parameters. The proposed technique is based on Numerical Inversion of Laplace Transform and does not require explicit presentation of the dynamic model in the form of set of differential equations. As a result, the moment vectors associated with frequency can be excluded when forming the moments subspace, leading to much smaller reduced models. In addition, the algorithm is highly parallelizable compared to time-stepping numerical integration techniques.
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页数：4
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