Using tapped delay line to improve the precision of an ensemble of classifiers in device-free localization

In this paper, we adopt a tapped delay line (TDL) equalizer as the arbiter of ensemble learning for device-free localization over IEEE 802.11 wireless local area network (WLAN). The proposed model is a two-stage decision process. While an input signal along with a delay line is given, a trained supp...

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Bibliographic Details
Published in2012 Conference on Precision electromagnetic Measurements pp. 656 - 657
Main Authors Wang-Hsin Hsu, Yi-Chen Li, Yi-Yuan Chiang, Jung-Shyr Wu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Bayesian classifier
Bayesian methods
Delay lines
device-free localization
ensemble learning
IEEE 802.11 Standards
Signal to noise ratio
suppor vector machine
Support vector machines
tapped delay line
Training
Wireless LAN
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Summary:In this paper, we adopt a tapped delay line (TDL) equalizer as the arbiter of ensemble learning for device-free localization over IEEE 802.11 wireless local area network (WLAN). The proposed model is a two-stage decision process. While an input signal along with a delay line is given, a trained support vector machine (SVM) and Bayesian classifier performs the first stage prediction. Then, the second stage decision selects the most frequent one among the intermediate outputs of stage one as the final output. Experimental results show the proposed method can not only to be as the arbiter of ensemble learning, but also significantly improve the precision to achieve 99.02%.
ISBN:1467304395
9781467304399
ISSN:0589-1485
2160-0171
DOI:10.1109/CPEM.2012.6251100