Optimizing Automatic Modulation Classification through Gaussian-Regularized Hybrid CNN-LSTM Architecture
This paper presents an innovative deep-learning model for Automatic Modulation Classification (AMC) in wireless communication systems. The proposed architecture integrates Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) networks, augmented by a Gaussian noise layer to mitigate o...
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| Główni autorzy: | , , |
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| Format: | Artigo |
| Język: | Árabe |
| Wydane: |
Assiut University, Faculty of Engineering
2024-07-01
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| Seria: | JES: Journal of Engineering Sciences |
| Hasła przedmiotowe: | |
| Dostęp online: | https://jesaun.journals.ekb.eg/article_353252_9803c299b84465206a9cc05705621ba6.pdf |
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