Neural inverse space mapping (NISM) optimization for EM-based microwave design

被引：30
|
作者：
Bandler, JW [1 ]
Ismail, MA
Rayas-Sánchez, JE
Zhang, QJ
机构：
[1] McMaster Univ, Simulat Optimizat Syst Res Lab, Hamilton, ON L8S 4K1, Canada
[2] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON L8S 4K1, Canada
[3] Carleton Univ, Dept Elect, Ottawa, ON K1S 5B6, Canada
[4] Bandler Corp, Dundas, ON L9H 5E7, Canada
来源：
INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING | 2003年 / 13卷 / 02期
关键词：
neural network applications; space mapping; optimization methods; design automation; EM optimization; neural space mapping; microwave circuits; microstrip filters; neural modeling;
D O I：
10.1002/mmce.10067
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
We present neural inverse space mapping (NISM) optimization for electromagnetics-based design of microwave structures. The inverse of the mapping from the fine to the coarse model parameter spaces is exploited for the first time in a space mapping algorithm. NISM optimization does not require up-front EM simulations, multipoint parameter extraction, or frequency mapping. It employs a simple statistical parameter extraction procedure. The inverse of the mapping is approximated by a neural network whose generalization performance is controlled through a network growing strategy. We contrast our new algorithm with neural space mapping (NSM) optimization. (C) 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 136-147, 2003.
引用
收藏
页码：136 / 147
页数：12
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