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Performance improvement of NN based RTLS by customization of NN structure: Heuristic approach
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2016 (English)In: Proceedings of the International Conference on Sensing Technology, ICST, IEEE Computer Society, 2016, Vol. 2016-March, 278-283 p.Conference paper (Refereed)
Abstract [en]

The purpose of this research is to improve performance of the Hybrid Scene Analysis - Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis is suitable to evaluate NN performance for different environmental conditions. Efficiency of the proposed customization of a Neural Network is verified by simulations and validated by physical experiments. This research also concerns the influence of size of Neural Network training set. The results prove that, better localization accuracy is with a NN system which is properly customized with respect to a training method, number of neurons and type of transfer function in the hidden layer and also type of transfer function in the output layer.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016. Vol. 2016-March, 278-283 p.
Series
Proceedings of the International Conference on Sensing Technology, ICST, ISSN 2156-8065
Keyword [en]
Algorithms; Complex networks; Heuristic methods; Network architecture; Neural networks; Optimization; Radio frequency identification (RFID); RSS; Transfer functions, Accuracy and precision; Environmental conditions; Indoor localization; Localization accuracy; Neural network training; Operating environment; Real-Time Locating Systems; Scene analysis, Indoor positioning systems
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-13146DOI: 10.1109/ICSensT.2015.7438407ScopusID: 2-s2.0-84964882100ISBN: 978-147996314-0 (print)OAI: oai:DiVA.org:bth-13146DiVA: diva2:1016257
Conference
9th International Conference on Sensing Technology, ICST 2015; Auckland; New Zealand
Note

Conference of 9th International Conference on Sensing Technology, ICST 2015 ; Conference Date: 8 December 2015 Through 11 December 2015; Conference Code:121054

Available from: 2016-10-04 Created: 2016-10-03 Last updated: 2016-11-08Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf