Radial Basis Function Neural Network Receiver Trained by Kalman Filter Including Evolutionary Techniques

Pedro Coelho, J. M. Do Amaral, A. Tome

2020

Abstract

Artificial Neural Networks have been broadly used in several domains of engineering and typical applications involving signal processing. In this paper a channel equalizer using radial basis function neural networks is proposed, on symbol by symbol basis. The radial basis function neural network is trained by an extended Kalman filter including evolutionary techniques. The key motivation for the equalizer application is the neural network capability to establish complex decision regions that are important for estimating the transmitted symbols appropriately. The neural network training process using evolutionary techniques including an extended Kalman filter enables a fast training for the radio basis function neural network. Simulation results are included comparing the proposed method with traditional ones indicating the suitability of the application.

Paper Citation

in Harvard Style

Coelho P., M. Do Amaral J. and Tome A. (2020). Radial Basis Function Neural Network Receiver Trained by Kalman Filter Including Evolutionary Techniques.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7, pages 626-631. DOI: 10.5220/0009565806260631

in Bibtex Style

@conference{iceis20,
author={Pedro Coelho and J. M. Do Amaral and A. Tome},
title={Radial Basis Function Neural Network Receiver Trained by Kalman Filter Including Evolutionary Techniques},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={626-631},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009565806260631},
isbn={978-989-758-423-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Radial Basis Function Neural Network Receiver Trained by Kalman Filter Including Evolutionary Techniques
SN - 978-989-758-423-7
AU - Coelho P.
AU - M. Do Amaral J.
AU - Tome A.
PY - 2020
SP - 626
EP - 631
DO - 10.5220/0009565806260631