Knowledge-based artificial neural network models for finline

被引：1

作者：

Li, C ^{[1
]}

Xu, J ^{[1
]}

Xue, LJ ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Inst Appl Phys, Chengdu 610054, Peoples R China

来源：

INTERNATIONAL JOURNAL OF INFRARED AND MILLIMETER WAVES | 2001年 / 22卷 / 02期

关键词：

artificial neural network; knowledge based; finline; millimeter wave;

D O I：

10.1023/A:1010760707665

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Finline plays an important role in millimeter-wave integrated-circuit design. In this paper, a knowledge-based artificial neural network is used to model the finline. Using prior knowledge input method and Bayesian regularization technique make the neural network models for finline reduce the amount of training data needed and prevent overfitting in neural network training. The neural network is electromagnetically developed with a set of training data that are produced by the finite element method, which is robust both from the angle of time of computation and accuracy.

引用

页码：351 / 359

页数：9

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