Artificial neural network models for the bend discontinuities in stripline circuits

被引：4

作者：

Hong, JS ^{[1
]}

Wang, BZ ^{[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 | 1999年 / 20卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Neural Network; Microwave; Training Data; Artificial Neural Network; Network Model;

D O I：

10.1023/A:1021773006977

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：

Stripline discontinuities are basic elements of many stripline circuits, such as the multilayer microwave monolithic ICs and the interconnect systems in highspeed digital circuits. Bend as one type of the stripline discontinuities will be modeled in this paper. A multilayer perceptron neural network(MLPNN) is used to model the bend discontinuities in stripline circuits. The MLPNN is electromagnetically developed with a set of training data that are produced by the full-wave finite-difference time-domain (FDTD) method. The full-factor design of experiments is used to determine the size of the training data.

引用

页码：1563 / 1579

页数：17

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