EMI Prediction of Packages by Deep Neural Network

被引：0

作者：

Jin, Hang ^{[1
]}

Ma, Hanzhi ^{[1
]}

Li, Er-Ping ^{[1
]}

机构：

[1] Zhejiang Univ, Coll Informat Sci & Elect Engn, Key Lab Adv Micronano Elect Devices & Smart Syst, Hangzhou, Zhejiang, Peoples R China

来源：

2018 JOINT IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY AND 2018 IEEE ASIA-PACIFIC SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY (EMC/APEMC) | 2018年

关键词：

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：

This paper presents advanced analysis and design methods such as the deep neural network (DNN) to predict the complex electromagnetic interference (EMI) radiation problems at the package level. Since the conventional analysis and design methods could not cope with the current EMI problems efficiently. The proposed DNN model can achieve good accuracy to predict EMI radiation.

引用

页码：72 / 72

页数：1

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