Detail publikace

ESTIMATION THE TRANSMISSION BETWEEN ANTENNAS USING ARTIFICIAL NEURAL NETWORKS IN THE UWB BAND

KOTOL, M. PROKEŠ, A. MIKULÁŠEK, T. RAIDA, Z.

Originální název

ESTIMATION THE TRANSMISSION BETWEEN ANTENNAS USING ARTIFICIAL NEURAL NETWORKS IN THE UWB BAND

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The characteristics of the transmission channel inside the car are very important for future intra-car communication technologies. These technologies will create the small wireless networks for the distribution of data services such as internet, video, audio, etc. transmission. For these services, it is preferable to use the UWB frequency band from 3 GHz to 11 GHz because of the hardware support availability. An estimation of transmission channel characteristic is time-consuming and computationally demanding process. Presented paper deals with the channel transfer function estimation for different receiving antenna locations determined by the two dimensional grid. Proposed artificial neural network used for the analysis of the transmission channel is based on the feed forward and radial basis function structure. Neural networks have been optimized using measured channel transfer function to achieve better effectiveness, speed and accuracy.

Klíčová slova

Artificial neural network, feed forward neural networks, radial basis function neural network, car, measurement, channel transmission function

Autoři

KOTOL, M.; PROKEŠ, A.; MIKULÁŠEK, T.; RAIDA, Z.

Vydáno

8. 8. 2016

Nakladatel

IEEE Xplore

ISBN

978-1-5090-6093-1

Kniha

2016 Progress in Electromagnetic Research Symposium (PIERS)

Strany od

1465

Strany do

1469

Strany počet

4

URL

BibTex

@inproceedings{BUT129207,
  author="Martin {Kotol} and Aleš {Prokeš} and Tomáš {Mikulášek} and Zbyněk {Raida}",
  title="ESTIMATION THE TRANSMISSION BETWEEN ANTENNAS USING ARTIFICIAL NEURAL NETWORKS IN THE UWB BAND",
  booktitle="2016 Progress in Electromagnetic Research Symposium (PIERS)",
  year="2016",
  pages="1465--1469",
  publisher="IEEE Xplore",
  doi="10.1109/PIERS.2016.7734683",
  isbn="978-1-5090-6093-1",
  url="http://ieeexplore.ieee.org/document/7734683/"
}