An End-To-End Neuromorphic Radio Classification System with an Efficient Sigma-Delta-Based Spike Encoding Scheme
- DOI
- 10.1109/tai.2023.3306334
- Published
- 2024-04
- Container
- IEEE Transactions on Artificial Intelligence
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/tai.2023.3306334,
title = {An End-To-End Neuromorphic Radio Classification System with an Efficient Sigma-Delta-Based Spike Encoding Scheme},
author = {Wenzhe Guo and Kuilian Yang and Haralampos-G. Stratigopoulos and Hassan Aboushady and Khaled Nabil Salama},
year = {2024},
journal = {IEEE Transactions on Artificial Intelligence},
doi = {10.1109/tai.2023.3306334},
url = {https://doi.org/10.1109/tai.2023.3306334}
}RIS
TY - JOUR TI - An End-To-End Neuromorphic Radio Classification System with an Efficient Sigma-Delta-Based Spike Encoding Scheme AU - Wenzhe Guo AU - Kuilian Yang AU - Haralampos-G. Stratigopoulos AU - Hassan Aboushady AU - Khaled Nabil Salama PY - 2024 JO - IEEE Transactions on Artificial Intelligence DO - 10.1109/tai.2023.3306334 UR - https://doi.org/10.1109/tai.2023.3306334 ER -
APA
Guo, W., Yang, K., Stratigopoulos, H., Aboushady, H., & Salama, K. N. (2024). An End-To-End Neuromorphic Radio Classification System with an Efficient Sigma-Delta-Based Spike Encoding Scheme. IEEE Transactions on Artificial Intelligence. https://doi.org/10.1109/tai.2023.3306334
Source records
- hal · retrieved 2026-11-10T11:58:51.915Z