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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Bibliografske podrobnosti

Principais autores:	Mohamed Elsagheer, Khairy Abd Elsayed, safwat Ramzy
Format:	Artigo
Jezik:	Árabe
Izdano:	Assiut University, Faculty of Engineering 2024-07-01
Serija:	JES: Journal of Engineering Sciences
Teme:	deep-learning automatic modulation classification cnn lstm snr
Online dostop:	https://jesaun.journals.ekb.eg/article_353252_9803c299b84465206a9cc05705621ba6.pdf
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