An Efficient Data Augmentation Method for Automatic Modulation Recognition from Low-Data Imbalanced-Class Regime

An Efficient Data Augmentation Method for Automatic Modulation Recognition from Low-Data Imbalanced-Class Regime

The application of deep neural networks to address automatic modulation recognition (AMR) challenges has gained increasing popularity. Despite the outstanding capability of deep learning in automatic feature extraction, predictions based on low-data regimes with imbalanced classes of modulation sign...

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Những tác giả chính: Shengyun Wei, Zhaolong Sun, Zhenyi Wang, Feifan Liao, Zhen Li, Haibo Mi
Định dạng: Bài viết
Ngôn ngữ:English
Được phát hành: MDPI AG 2023-03-01
Loạt:Applied Sciences
Những chủ đề:
automatic modulation recognition (AMR)
deep learning
data augmentation
low-data regime
imbalanced-class
Truy cập trực tuyến:https://www.mdpi.com/2076-3417/13/5/3177

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https://www.mdpi.com/2076-3417/13/5/3177

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