Naslov
A Comparison of Neural Network Models for Indoor Field Strength Prediction

Autori
Vilović, Ivan ; Burum, Nikša ; Šipuš, Zvonimir

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

Izvornik
Proceedings of ELMAR 2007 / Grgić, Mislav ; Grgić, Sonja - Zadar, 2007, 95-98

Skup
49th International Symposium ELMAR-2007 focused on Multimedia Signal Processing and Communications

Mjesto i datum
Zadar, Hrvatska, 12.09.2007. - 14.09.2007

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neural network; Radial Basis Function Network; Ray Tracing; Multilayer Perceptron; Training algorithm

Sažetak
This paper presents a comparison of the field strength prediction in indoor environments based on ray tracing, multilayer perceptron and radial basis function networks. It has been already shown for neural networks as powerful tool in RF propagation prediction. It is very important to choose proper algorithm for training a neural network, so we compared several training algorithms for the case of multilayer perceptron model. As the case used a corridor of university building in Dubrovnik, for which calculation, simulation and measurement of signal strength were obtained. The results show an improvement in field strength prediction with neural models over conventional models if training algorithm and neural network architecture are carefully chosen. The best results are obtained by the radial basis function neural network model.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

POVEZANOST RADA