基于深度学习的带内干扰检测与分类

IF 2 3区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Andreas Andersson, Patrik Eliardsson, Erik Axell, Kristoffer Hägglund, Kia Wiklundh
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本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning-Based In-Band Interference Detection and Classification
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来源期刊
CiteScore
4.80
自引率
19.00%
发文量
235
审稿时长
2.3 months
期刊介绍: IEEE Transactions on Electromagnetic Compatibility publishes original and significant contributions related to all disciplines of electromagnetic compatibility (EMC) and relevant methods to predict, assess and prevent electromagnetic interference (EMI) and increase device/product immunity. The scope of the publication includes, but is not limited to Electromagnetic Environments; Interference Control; EMC and EMI Modeling; High Power Electromagnetics; EMC Standards, Methods of EMC Measurements; Computational Electromagnetics and Signal and Power Integrity, as applied or directly related to Electromagnetic Compatibility problems; Transmission Lines; Electrostatic Discharge and Lightning Effects; EMC in Wireless and Optical Technologies; EMC in Printed Circuit Board and System Design.
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