{"ID":2846191,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.02493","arxiv_id":"2511.02493","title":"Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications","abstract":"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.","short_abstract":"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 cal...","url_abs":"https://arxiv.org/abs/2511.02493","url_pdf":"https://arxiv.org/pdf/2511.02493v1","authors":"[\"Ana Pérez-Neira\",\"Marc Martinez-Gost\",\"Miguel Ángel Lagunas\"]","published":"2025-11-04T11:31:41Z","proceeding":"eess.SP","tasks":"[\"eess.SP\",\"eess.SY\"]","methods":"[]","has_code":false}