Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network

In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks (CNNs) or recurrent neural networks (RNNs). Howev...

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Detalles Bibliográficos
Autores principales: Wang, Dong, Lin, Meiyan, Zhang, Xiaoxu, Huang, Yonghui, Zhu, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459892/
https://www.ncbi.nlm.nih.gov/pubmed/37631817
http://dx.doi.org/10.3390/s23167281

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459892/
https://www.ncbi.nlm.nih.gov/pubmed/37631817
http://dx.doi.org/10.3390/s23167281

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