On projection-based algorithms for model-order reduction of interconnects
On projection-based algorithms for model-order reduction of interconnects
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DOI：
10.1109/tcsi.2002.804542
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发表时间：
2002-12
影响因子：
5.1
通讯作者：
Janet M. Wang;C. Chu;Qingjian Yu;E. Kuh
中科院分区：
文献类型：
--
作者：
Janet M. Wang;C. Chu;Qingjian Yu;E. Kuh
模型阶数降阶是实现互连网络快速仿真的关键技术。在众多的模型阶约简算法中，基于投影法的模型阶约简算法效果较好。在本文中，我们回顾了两类基于投影的算法。第一个是系数匹配算法。将单点矩匹配的Krylov子空间方法推广到匹配点位于复平面闭合右侧任意位置的多点矩匹配方法，并给出了Hilbert和Hardy空间中基于标准正交多项式和广义标准正交基函数的级数展开系数匹配算法。第二类是基于语法的算法，我们为语法的计算提供了高效的算法和新的基于近似语法的方法。我们总结了基于投影的算法的一些重要性质，以便更灵活地使用它们。
Model-order reduction is a key technique to do fast simulation of interconnect networks. Among many model-order reduction algorithms, those based on projection methods work quite well. In this paper, we review the projection-based algorithms in two categories. The first one is the coefficient matching algorithms. We generalize the Krylov subspace method on moment matching at a single point, to multipoint moment-matching methods with matching points located anywhere in the closed right-hand side (RHS) of the complex plane, and we provide algorithms matching the coefficients of series expansion-based on orthonormal polynomials and generalized orthonormal basis functions in Hilbert and Hardy space. The second category belongs to the grammian-based algorithms, where we provide efficient algorithm for the computation of grammians and new approximate grammian-based approaches. We summarize some important properties of projection-based algorithms so that they may be used more flexibly.