A recurrent neural network for inter-localization of mobile phones

Shuai Li, S. Chen, Y. Lou, B. Lu, Y. Liang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

Abstract

The fact that most mobile phones are equipped with short-range communication devices, such as Bluetooth, etc., and a portion of mobile phones have GPS embedded enables us to envision to roughly localize GPS-free phones recursively and progressively by exploiting the available information. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem as an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. Two applications examples are considered and simulated. Simulations demonstrate the effectiveness of the proposed method.
Original languageEnglish
Title of host publication2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs
Publication statusPublished - 22 Aug 2012
Externally publishedYes
Event2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia
Duration: 10 Jun 201215 Jun 2012

Conference

Conference2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
CountryAustralia
CityBrisbane, QLD
Period10/06/1215/06/12

Keywords

  • Bluetooth
  • localization
  • mobile phone
  • Recurrent neural network

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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