A Machine Learning Approach to Predict Supply and Temperature Variation Aware RF Integrated Circuit Interference Limitation-Reference-Cited by-同舟云学术

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A Machine Learning Approach to Predict Supply and Temperature Variation Aware RF Integrated Circuit Interference Limitation

Published:2020-08-26 Issue: Volume: Page:
ISSN:
Container-title:2020 International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)
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Author:

Chang Michael

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9237368/9237388/09237389.pdf?arnumber=9237389

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extrapolation With Range Determination of 2-D Spectral Transposed Convolutional Neural Network for Advanced Packaging Problems;IEEE Transactions on Components, Packaging and Manufacturing Technology;2023-10

2. Electromagnetic Pattern Cluster in Latent Space in Near Filed Scanning of a Device;Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence;2022-12-23

3. Radio Frequency Interference Characterization of 5G Device with Reciprocity Theorem;2022 IEEE Electrical Design of Advanced Packaging and Systems (EDAPS);2022-12-12

4. An EMI radiation grouping approach based on spectral cluster in near filed scanning for assessment;IOP Conference Series: Materials Science and Engineering;2021-11-01

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