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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Bibliographic Details
Main Authors: Shengyun Wei, Zhaolong Sun, Zhenyi Wang, Feifan Liao, Zhen Li, Haibo Mi
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Applied Sciences
Subjects:
automatic modulation recognition (AMR)
deep learning
data augmentation
low-data regime
imbalanced-class
Online Access:https://www.mdpi.com/2076-3417/13/5/3177

Internet

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

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