Yield-driven electromagnetic optimization via space mapping-based neuromodels

被引：44
作者：
Bandler, JW [1 ]
Rayas-Sánchez, JE
Zhang, QJ
机构：
[1] McMaster Univ, Simulat Opt Syst Res Lab, Hamilton, ON L8S 4K1, Canada
[2] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON L8S 4K1, Canada
[3] Bandler Corp, Dundas, ON L9H 5E7, Canada
[4] Carleton Univ, Dept Elect, Ottawa, ON K1S 5B6, Canada
来源：
INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING | 2002年 / 12卷 / 01期
关键词：
neural network applications; space mapping; optimization methods; design automation; EM optimization; neural space mapping; statistical analysis; yield optimization; design centering; microwave circuits; microstrip filters; neural modeling;
D O I：
10.1002/mmce.10015
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Accurate yield optimization and statistical analysis of microwave components are crucial ingredients for manufacturability-driven designs in a time-to-market development environment. Yield optimization requires intensive simulations to cover the entire statistic of possible outcomes of a given manufacturing process. Performing direct yield Optimization using accurate full-wave electromagnetic simulations does not appear feasible. In this article, an efficient procedure to realize electromagnetics (EM) based yield optimization and statistical analysis of microwave structures using space mapping-based neuromodels is proposed. Our technique is illustrated by the EM-based statistical analysis and yield optimization of a high temperature superconducting (HTS) microstrip filter. (C) 2002 John Wiley & Sons, Inc.
引用
收藏
页码：79 / 89
页数：11
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