Neural network models for finline discontinuities

被引：2

作者：

Jin, L ^{[1
]}

Ruan, CL ^{[1
]}

机构：

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

来源：

INTERNATIONAL JOURNAL OF INFRARED AND MILLIMETER WAVES | 2004年 / 25卷 / 12期

关键词：

millimeterwave transmission line; finline discontinuity; radial basis function; EM-ANN;

D O I：

10.1007/s10762-004-0203-1

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：

The radial basis network is used as the finline discontinuities electromagnetic artificial neural network(EM-ANN) models. EM software analysis is employed to characterize finline discontinuities. EM ANN models are then trained using physical parameters and frequency as inputs and equivalent electric circuit element parameters of finline discontinuities as outputs. Once trained, the EM-ANN models can simulate equivalent electric circuit element parameters of finline step, notch and strip very fast and efficiently.

引用

页码：1819 / 1827

页数：9

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