Joint Sparse Recovery Using Deep Unfolding With Application to Massive Random Access-Reference-Cited by-同舟云学术

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Joint Sparse Recovery Using Deep Unfolding With Application to Massive Random Access

Published:2020-05 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Sabulal Anand P.,Bhashyam Srikrishna

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9040208/9052899/09053312.pdf?arnumber=9053312

Cited by 8 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. Iteratively Preconditioned Guidance of Denoising (Diffusion) Models For Image Restoration;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. DECONET: An Unfolding Network for Analysis-Based Compressed Sensing With Generalization Error Bounds;IEEE Transactions on Signal Processing;2023

3. Model-Based Deep Learning for Joint Activity Detection and Channel Estimation in Massive and Sporadic Connectivity;IEEE Transactions on Wireless Communications;2022-11

4. Learning-Based Sparse Recovery for Joint Activity Detection and Channel Estimation in Massive Random Access Systems;IEEE Wireless Communications Letters;2022-11

5. Parallel Greedy Search for Random Access in Wireless Networks;IETE Technical Review;2022-09-14

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