一种补偿宏模型无源性的快速凸优化方法

doi:10.3969/j.issn.1001-2400.2012.01.012

J4 ›› 2012, Vol. 39 ›› Issue (1): 62-66+121.doi: 10.3969/j.issn.1001-2400.2012.01.012

一种补偿宏模型无源性的快速凸优化方法

高崧;李玉山;闫旭

(西安电子科技大学电路CAD研究所，陕西西安 710071)

收稿日期:2010-11-04 出版日期:2012-02-20 发布日期:2012-04-06
通讯作者: 高崧
作者简介:高崧(1984-)，男，西安电子科技大学博士研究生，E-mail: gaosong1984@gmail.com．
基金资助:
国家自然科学基金资助项目(60672027,60871072);教育部博士点基金资助项目(20050701002)

Fast convex optimization method for passivity enforcement of macromodels

GAO Song;LI Yushan;YAN Xu

(Research Inst. of Electronic CAD, Xidian Univ., Xi'an 710071， China)

Received:2010-11-04 Online:2012-02-20 Published:2012-04-06
Contact: GAO Song

摘要/Abstract

摘要：

针对传统凸优化方法的自由变量个数大、计算复杂度高的缺点，提出了一种快速的凸优化方法．在优化之前先确定能量函数矩阵的初始值，并给予适当的自由度，使自由变量的个数降低60％以上，从而大大提高了计算效率．实验结果表明，在保证模型精度的前提下，该方法的仿真时间小于传统凸优化方法的1/30．

关键词: 信号完整性, 宏模型, 无源性补偿, 代数Riccati方程, 凸优化

Abstract:

In the traditional convex optimization based method, the number of free variables is large, which will lead to demanding computations. Based on this consideration, a fast convex optimization method is proposed in this paper. The initial value of the energy matrix is determined before optimization with only some degrees of freedom. This procedure can reduce 60％ of the number of free variables, which can greatly increase the efficiency of the method. Numerical examples show that the simulation time required by the proposed method is less than 1/30 that of the traditional method with high accuracy.

Key words: signal integrity, macromodel, passivity enforcement, algebraic Riccati equation, convex optimization

高崧;李玉山;闫旭. 一种补偿宏模型无源性的快速凸优化方法[J]. J4, 2012, 39(1): 62-66+121.

GAO Song;LI Yushan;YAN Xu. Fast convex optimization method for passivity enforcement of macromodels[J]. J4, 2012, 39(1): 62-66+121.

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一种补偿宏模型无源性的快速凸优化方法

Fast convex optimization method for passivity enforcement of macromodels

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