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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Vydané v:	IEEE sensors journal Ročník 25; číslo 21; s. 40877 - 40891
Hlavní autori:	Tan, Benying, Wang, Manman, Li, Yujie, Lu, Yongyun, Ding, Shuxue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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