Unsupervised Modulation Recognition Method Based on Multi-Domain Representation Contrastive Learning-Reference-Cited by-同舟云学术

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Unsupervised Modulation Recognition Method Based on Multi-Domain Representation Contrastive Learning

Published:2023-11-14 Issue: Volume:1 Page:1-6
ISSN:
Container-title:2023 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)
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Author:

Li Yu¹,Shi Xiaoran¹,Yang Xinyao¹,Zhou Feng¹

Affiliation:

1. Xidian University,Key Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education,Xi'an,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10400066/10400207/10400274.pdf?arnumber=10400274

Reference16 articles.

1. Automatic Modulation Classification Using Contrastive Fully Convolutional Network

2. Deep Neural Network for Robust Modulation Classification Under Uncertain Noise Conditions

3. Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

4. Deep learning based automatic modulation recognition: Models, datasets, and challenges

5. Language Models are Few-Shot Learners;Brown;Advances in neural infor mation processing systems,2020

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