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Published September 4, 2025 | Version v1
Conference paper Open

Deep Unfolding of Atomic Norm Minimization for DoA Estimation

Authors/Creators

  • Raza, Ali1 ORCID icon
  • Nguyen, Nhan1 ORCID icon
  • Juntti, Markku1 ORCID icon
  • 1. ROR icon University of Oulu

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  • OpenAIRE

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Keywords and subjects

Keywords

  • direction of arrival (DOA)
  • projected gradient descent (PGD)
  • atomic norm minimization
  • anm
  • deep unfolding
  • deep learning

Details

DOI
10.1109/SPAWC66079.2025.11143326
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DOI 

10.1109/SPAWC66079.2025.11143326

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[![DOI](https://zenodo.org/badge/DOI/10.1109/SPAWC66079.2025.11143326.svg)](https://doi.org/10.1109/SPAWC66079.2025.11143326)

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Resource type
Conference paper
Publisher
IEEE
Conference
2025 IEEE Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC) , Surrey, UK, 7-10 July 2025

Rights

License
cc-by-4.0 icon Creative Commons Attribution 4.0 International
The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more

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Technical metadata

Created
April 9, 2026
Modified
April 9, 2026

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