Wireless Signal Denoising Using Conditional Generative Adversarial Networks-Reference-Cited by-同舟云学术

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Wireless Signal Denoising Using Conditional Generative Adversarial Networks

Published:2023-05-20 Issue: Volume: Page:
ISSN:
Container-title:IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
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Author:

Tang Haolin¹,Zhao Yanxiao¹,Wang Guodong²,Luo Changqing³,Wang Wei⁴

Affiliation:

1. Virginia Commonwealth University,Department of Electrical and Computer Engineering,Richmond,VA,USA

2. Massachusetts College of Liberal Arts,Department of Computer Science,North Adams,MA,USA

3. Virginia Commonwealth University,Department of Computer Science,Richmond,VA,USA

4. San Diego State University,Department of Computer Science,San Diego,CA,USA

Funder

Virginia Commonwealth University (VCU) Presidential Research Quest Fund (PeRQ)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10225747/10225748/10225927.pdf?arnumber=10225927

Reference18 articles.

1. Research and Application of Denoising Method Based on Wavelet Threshold

2. A new pre-whitening transform domain LMS algorithm and its application to speech denoising

3. GAN-Based Noise Model for Denoising Real Images

4. Using AutoEncoders for Radio Signal Denoising

5. Conditional generative adversarial nets;mirza;ArXiv Preprint,2014

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-Agent RL-Based Industrial AIGC Service Offloading over Wireless Edge Networks;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS);2024-05-20

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