Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866917059563094016 |
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| author | Pérez-Neira, Ana Martinez-Gost, Marc Lagunas, Miguel Ángel |
| author_facet | Pérez-Neira, Ana Martinez-Gost, Marc Lagunas, Miguel Ángel |
| contents | There is an urgent reflection on traditional nonlinear signal processing methods in communications before Artificial Intelligence (AI) dominates the field. It implies a need to reassess or reinterpret established theories and tools, highlighting the tension between data-driven and model-based approaches. This paper calls for preserving valuable insights from classical signal processing while exploring how they can coexist or integrate with emerging AI methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_02493 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications Pérez-Neira, Ana Martinez-Gost, Marc Lagunas, Miguel Ángel Signal Processing Systems and Control There is an urgent reflection on traditional nonlinear signal processing methods in communications before Artificial Intelligence (AI) dominates the field. It implies a need to reassess or reinterpret established theories and tools, highlighting the tension between data-driven and model-based approaches. This paper calls for preserving valuable insights from classical signal processing while exploring how they can coexist or integrate with emerging AI methods. |
| title | Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications |
| topic | Signal Processing Systems and Control |
| url | https://arxiv.org/abs/2511.02493 |