Improved Deep Residual Shrinkage Network for Intelligent Interference Recognition with Unknown Interference

In complex battlefield environments, flying ad-hoc network (FANET) faces challenges in manually extracting communication interference signal features, a low recognition rate in strong noise environments, and an inability to recognize unknown interference types. To solve these problems, one simple no...

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Detalles Bibliográficos
Autores principales: Wu, Xiaojun, Zhou, Yibo, Wu, Daolong, Xiao, Haitao, Lu, Yaya, Li, Hanbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534624/
https://www.ncbi.nlm.nih.gov/pubmed/37765966
http://dx.doi.org/10.3390/s23187909

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534624/
https://www.ncbi.nlm.nih.gov/pubmed/37765966
http://dx.doi.org/10.3390/s23187909

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