Modeling of Electromagnetic Disturbance Characteristics of Bus Network Protocol Chip

The study introduces a quantitative model that primarily endeavors to analyze and forecast the conducted emission behaviors of several archetypal digital devices. Through rigorous testing of the conducted emissions from representative digital chips, a model for the conducted emissions of digital integrated circuit chips is constructed, drawing upon the test outcomes. The Power Delivery Network model is acquired employing vector fitting techniques, whereas the chip's internal source model is deduced via indirect measurement methods. The comparative analysis reveals that the quantitative model's error margin remains within 3dB of the actual measured data, demonstrating its high degree of accuracy.

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Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1109/mape62875.2024.10813912
Citations
1
Primary Topic
Internet of Things and Social Network Interactions
Type
article
Field-Weighted Citation Impact
0.35
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article

Modeling of Electromagnetic Disturbance Characteristics of Bus Network Protocol Chip

Siyi Xing, Changshun Fu, Zhaowen Yan, Yunxiang Jia et al.
1 citations
Internet of Things and Social Network Interactions
0.35
article

Modeling of Electromagnetic Disturbance Characteristics of Bus Network Protocol Chip

Siyi Xing, Changshun Fu, Zhaowen Yan, Yunxiang Jia, Jiaxing Ge, Xingyu Li
article en
1 citations

Abstract

The study introduces a quantitative model that primarily endeavors to analyze and forecast the conducted emission behaviors of several archetypal digital devices. Through rigorous testing of the conducted emissions from representative digital chips, a model for the conducted emissions of digital integrated circuit chips is constructed, drawing upon the test outcomes. The Power Delivery Network model is acquired employing vector fitting techniques, whereas the chip's internal source model is deduced via indirect measurement methods. The comparative analysis reveals that the quantitative model's error margin remains within 3dB of the actual measured data, demonstrating its high degree of accuracy.

Beihang University (CN)
Affordable and clean energy
Openalex Percentile: Top 35%
Internet of Things and Social Network Interactions
0.35
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