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

Wang Hsin Hsu, Yi Chen Li, Yi Yuan Chiang, Jung Shyr Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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%.

Original languageEnglish
Title of host publication2012 Conference on Precision Electromagnetic Measurements, CPEM 2012
Pages656-657
Number of pages2
DOIs
StatePublished - 2012
Event2012 Conference on Precision Electromagnetic Measurements, CPEM 2012 - Washington, DC, United States
Duration: 1 Jul 20126 Jul 2012

Publication series

NameCPEM Digest (Conference on Precision Electromagnetic Measurements)
ISSN (Print)0589-1485

Conference

Conference2012 Conference on Precision Electromagnetic Measurements, CPEM 2012
Country/TerritoryUnited States
CityWashington, DC
Period1/07/126/07/12

Keywords

  • Bayesian classifier
  • device-free localization
  • ensemble learning
  • suppor vector machine
  • tapped delay line

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