Prediction of IC Equivalent Magnetic Dipoles Using Deep Convolutional Neural Network

被引:0
作者
Ma, Hanzhi [1 ]
Li, Er-Ping [1 ]
机构
[1] Zhejiang Univ, UIUC Inst, Dept Elect Engn, ZJU, Hangzhou, Zhejiang, Peoples R China
来源
2018 IEEE ELECTRICAL DESIGN OF ADVANCED PACKAGING AND SYSTEMS SYMPOSIUM (EDAPS 2018) | 2018年
关键词
Equipvalent magnetic dipole model; convolutional neural network; electromagnetic interference; IC electromagnetic radiation source restruction;
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
The equivalent dipole model based on near electromagnetic field scanning can be used for electromagnetic interference sources reconstruction without considering the specific circuit structure. This paper presents a new method for predicting the equivalent magnetic dipole by deep convolutional neural network for simulation of IC electromagnetic radiation. The numerical testing results demonstrate that the equivalent magnetic dipole array predicted by CNN can produce the original radiation field effectively.
引用
收藏
页数:3
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