Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design of hand-crafted expert features. With the intui...
Main Authors: | Kaisheng Liao, Yaodong Zhao, Jie Gu, Yaping Zhang, Yi Zhong |
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Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9330604/ |
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