Symbol decision equalizer using a radial basis functions neural network

Authors:
Corina Botoca;Georgeta Budura
Affiliations:
Communications Department, "Politehnica" University of Timisoara, Timisoara, Romania;Communications Department, "Politehnica" University of Timisoara, Timisoara, Romania
Venue:
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
Year:
2006

Citing 11
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Abstract

This paper presents the problem of multiple quadrature amplitude modulated signals equalization and argues the use of a radial basis functions neural network (RBF-NN) equalizer. Different competitive learning algorithms for the RBF-NN centres determination are discussed. A new competitive learning algorithm is introduced, the rival penalized competitive learning, which rewards the winner and penalizes its first rival. The results of simulations performed in different conditions, are presented showing that the performance of the RBF-NN equalizer, which is based on this new algorithm, is better if compared with other competitive algorithms.