A Novel Lightweight Grouped Gated Recurrent Unit for Automatic Modulation Classification-Reference-Cited by-同舟云学术

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A Novel Lightweight Grouped Gated Recurrent Unit for Automatic Modulation Classification

Published:2024-08 Issue:8 Volume:13 Page:2135-2139
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Hu Xin¹^ORCID,Gao Gujiuxiang¹^ORCID,Li Boyan¹^ORCID,Wang Weidong¹^ORCID,Ghannouchi Fadhel M.²^ORCID

Affiliation:

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China

2. Department of Electrical and Computer Engineering, Intelligent RF Radio Laboratory, Schulish School of Engineering, University of Calgary, Calgary, AB, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962382/10633211/10534861.pdf?arnumber=10534861

Reference15 articles.

1. Deep Learning Based Modulation Recognition With Multi-Cue Fusion

2. Convolutional Radio Modulation Recognition Networks

3. Deep neural network architectures for modulation classification

4. A Comparison of LSTM and GRU Networks for Learning Symbolic Sequences

5. Automatic modulation classification using recurrent neural networks

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