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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Bibliographic Details

Published in:	Digital communications and networks Vol. 10; no. 5; pp. 1448 - 1458
Main Authors:	Zhou, Huaji, Bai, Jing, Wang, Yiran, Ren, Junjie, Yang, Xiaoniu, Jiao, Licheng
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.10.2024 KeAi Communications Co., Ltd
Subjects:	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
Online Access:	Get full text
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