EMI Radiation Prediction and Structure Optimization of Packages by Deep Learning

EMI Radiation Prediction and Structure Optimization of Packages by Deep Learning

With a rapid increase in operating frequency and package complexity, conventional analysis methods cannot efficiently cope with current complex electromagnetic interference (EMI) issues. In this paper, a new method built on a deep neural network (DNN) model is proposed to accurately and rapidly pred...

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Bibliographic Details
Main Authors: Hang Jin, Hanzhi Ma, Mark D. Butala, En-Xiao Liu, Er-Ping Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep learning algorithm
deep neural network
electromagnetic interference
radiation prediction
sensitivity analysis
structure optimization
Online Access:https://ieeexplore.ieee.org/document/8758619/

Internet

https://ieeexplore.ieee.org/document/8758619/

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