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Abstract
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.
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Authors (3)
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Wlodek Kulesza
- Blekinge Institute of Technology Institute of Applied Signal Processing
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- 2015 9th International Conference on Sensing Technology (ICST) strony 278 - 283
- Language:
- English
- Publication year:
- 2015
- Bibliographic description:
- Jachimczyk B., Dziak D., Kulesza W.: Performance improvement of NN based RTLS by customization of NN structure - heuristic approach// 2015 9th International Conference on Sensing Technology (ICST)/ : , 2015, s.278-283
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/icsenst.2015.7438407
- Verified by:
- Gdańsk University of Technology
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