An Accurate and Robust Approach of Device-Free Localization With Convolutional Autoencoder

Device-free localization (DFL), as an emerging technology that locates targets without any attached devices via wireless sensor networks, has spawned extensive applications in the Internet of Things (IoT) field. For DFL, a key problem is how to extract significant features to characterize raw signal...

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Veröffentlicht in:	IEEE internet of things journal Jg. 6; H. 3; S. 5825 - 5840
Hauptverfasser:	Zhao, Lingjun, Huang, Huakun, Li, Xiang, Ding, Shuxue, Zhao, Haoli, Han, Zhaoyang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.06.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Classification Communication system security Convolution convolution autoencoder (CAE) deep learning device-free localization (DFL) Electronic devices Feature extraction Image classification Internet of Things Localization Neural networks New technology Noise Noise levels Random noise Remote sensors Robustness Signal to noise ratio Wireless communication wireless sensor network (WSN) Wireless sensor networks
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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