Sparse and passive reduced-order interconnect modeling by eigenspace method

被引:0
作者
Tanji, Yuichi [1 ]
机构
[1] Kagawa Univ, Dept Reliabil Based Informat Syst Engn, Takamatsu, Kagawa 7610396, Japan
关键词
model order reduction; passivity; eigen decomposition; truncated balanced realization; Krylov subspace method;
D O I
10.1093/ietfec/e91-a.9.2419
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The passive and sparse reduced-order modeling of a RLC network is presented, where eigenvalues and eigenvectors of the original network are used, and thus the obtained macromodel is more accurate than that provided by the Krylov subspace methods or TBR procedures for a class of circuits. Furthermore, the proposed method is applied to low pass filtering of a reduced-order model produced by these methods without breaking the passivity condition. Therefore, the proposed eigenspace method is not only a reduced-order macromodeling method, but also is embedded in other methods enhancing their performances.
引用
收藏
页码:2419 / 2425
页数:7
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