保证全局有理逼近宏建模的无源性和顺序自动选择

A. Hillegonds, K. Melde, J. Prince
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引用次数: 0

摘要

今天的数字和无线设计要求越来越高的频率和更好的性能。随着整体模型复杂性的增长,开发准确、高效的互连仿真工具变得更加重要。一种常见的方法是使用网络的频域宏模型。本文主要研究Elzinga (Elzinga, 2000)开发的方法中的全局有理逼近宏观建模技术。在这里,通过对只发生轻微被动性冲突的宏模型实施被动性,该技术得到了改进。此外,还开发了一种改进的有理多项式的自动选序方法,并将其应用于(Elzinga, 2000)的具体程序中对该方法进行了测试
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ensuring passivity and automatic order selection for global rational approximation macromodeling
Today digital and wireless designs demand both increasingly higher frequencies and better performance. As overall model complexity grows, greater importance is placed on the development of accurate, efficient interconnect simulation tools. One common approach is to use frequency domain macromodels of the network. This paper concentrates on the global rational approximation macromodeling technique as in the method developed by Elzinga (Elzinga, 2000). Here the technique is improved upon by enforcing passivity for macromodels where only minor passivity violations occur. In addition, an improved automated order selection method for the rational polynomial was developed and applied to the specific program of (Elzinga, 2000) to test the method
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