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Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture
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| Published in: | Advanced Intelligent Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1871928184962809856 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Advanced Intelligent Systems |
| description | |
| discipline_display | Artificial Intelligence |
| discipline_facet | Artificial Intelligence |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:107359 |
| institution | FRELIP |
| journal_source_facet | Advanced Intelligent Systems |
| last_indexed | 2026-07-28T03:37:11.960Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture Artificial Intelligence General Artificial Intelligence |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Artificial Intelligence General Artificial Intelligence |
| subject_facet | Artificial Intelligence General Artificial Intelligence |
| title | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_alt | Superando el problema de discontinuidad de fase en la optimización de RIS: un marco robusto y escalable de regresión profunda consciente de fase mediante arquitectura híbrida CNN-LSTM Surmonter le problème de discontinuité de phase dans l'optimisation RIS : un cadre de régression profonde robuste et évolutif conscient de la phase via une architecture hybride CNN-LSTM Superando o Problema de Descontinuidade de Fase na Otimização de RIS: Uma Estrutura de Regressão Profunda Robusta e Escalável Ciente de Fase via Arquitetura Híbrida CNN-LSTM |
| title_auth | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_es_txt | Superando el problema de discontinuidad de fase en la optimización de RIS: un marco robusto y escalable de regresión profunda consciente de fase mediante arquitectura híbrida CNN-LSTM |
| title_fr_txt | Surmonter le problème de discontinuité de phase dans l'optimisation RIS : un cadre de régression profonde robuste et évolutif conscient de la phase via une architecture hybride CNN-LSTM |
| title_full | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_fullStr | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_full_unstemmed | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_pt_txt | Superando o Problema de Descontinuidade de Fase na Otimização de RIS: Uma Estrutura de Regressão Profunda Robusta e Escalável Ciente de Fase via Arquitetura Híbrida CNN-LSTM |
| title_short | Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture |
| title_sort | overcoming the phase discontinuity problem in ris optimization: a robust and scalable phase‐aware deep regression framework via hybrid cnn–lstm architecture |
| topic | Artificial Intelligence General Artificial Intelligence |
| url | https://advanced.onlinelibrary.wiley.com/doi/10.1002/aisy.70460?af=R |