Introduction of Artificial Neural Networks in EMC

被引：0

作者：

Burghardt, Felix ^{[1
]}

Garbe, Heyno ^{[1
]}

机构：

[1] Leibniz Univ Hannover, Inst Elect Engn & Measurement Technol, Hannover, Germany

来源：

2018 IEEE SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY, SIGNAL INTEGRITY AND POWER INTEGRITY (EMC, SI & PI) | 2018年

关键词：

artificial neural network; prediction; backpropagation;

D O I：

暂无

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：

Electromagnetic examinations are usually very expensive. Every simulation needs time for computation and every measurement needs time for preparation. In addition, similar results are generally expected when examining similar objects. If the relation between the differences of investigated objects and their results could be found, a prediction on objects which are not yet examined would be possible. In this paper, a method based on artificial neural networks will be presented, with which a prediction of simulation results of similar objects is possible.

引用

页码：165 / 169

页数：5

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