A Deep Dictionary Learning Framework for Device-Free Localization Based on Nonconvex Sparse Regularization and DC Programming

Received signal strength (RSS)-based device-free localization (DFL) is commonly used in the Internet-of-Things (IoT) field. However, the current DFL algorithms have limitations in terms of stability and accuracy, which hinders the widespread application of DFL. Current research on DFL predominantly...

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Veröffentlicht in:	IEEE sensors journal Jg. 25; H. 21; S. 40877 - 40891
Hauptverfasser:	Tan, Benying, Wang, Manman, Li, Yujie, Lu, Yongyun, Ding, Shuxue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Data mining Data models Datasets Deep dictionary learning (DDL) Deep learning device-free localization (DFL) Dictionaries difference-of-convex (DC) programming Feature extraction Internet of Things Localization Location awareness Machine learning nonconvex sparse regularization received signal strength (RSS) Regularization Representations Signal strength Sparse approximation Wireless sensor networks
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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