Deep radio signal clustering with interpretability analysis based on saliency map

With the development of information technology, radio communication technology has made rapid progress. Many radio signals that have appeared in space are difficult to classify without manually labeling. Unsupervised radio signal clustering methods have recently become an urgent need for this situat...

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Vydané v:	Digital communications and networks Ročník 10; číslo 5; s. 1448 - 1458
Hlavní autori:	Zhou, Huaji, Bai, Jing, Wang, Yiran, Ren, Junjie, Yang, Xiaoniu, Jiao, Licheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.10.2024 KeAi Communications Co., Ltd
Predmet:	Autoencoder Clustering features visualization Deep learning interpretability Unsupervised radio signal clustering Clustering features visualization Unsupervised radio signal clustering Autoencoder Deep learning interpretability
ISSN:	2352-8648, 2352-8648
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