Naslov
A Comparison of MLP and RBF Neural Network Architectures for Location Determination in Indoor Environments

Autori
Vilović, Ivan ; Burum, Nikša

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
7th European Conference on antennas and Propagation, Gthenborg/Sweden, 2013. / Per-Simon Kildal - Gothenburg, 2013, 338-341

ISBN
978-88-907018-1-8

Skup
7th European Conference on antennas and Propagation, Eucap 2013, Gthenborg/Sweden, 2013.

Mjesto i datum
Göteborg, Švedska, 08.04.2013. - 12.04.2013

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neural network; MLP network; RBF network; indoor environment; localization determination

Sažetak
In this paper two different neural network architectures are investigated for enough accurate position determination of a mobile device in the complex indoor environment. The investigation includes multilayer perceptron (MLP) and radial basis function (RBF) neural networks. It has been already shown for neural networks as powerful tool in RF propagation prediction. The research is based on dependence of the received signal with distance. The neural networks are trained by three training algorithms: scaled conjugate, resilient backpropagation and Levenberg-Marquardit with Bayesian regularization. The obtained results for position prediction show error that is less than 0.25 m.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

POVEZANOST RADA